Flipping for Felonies

The mortgage meltdown was brought on by fraud and corruption at all levels.

At the grassroots in Cleveland, Ohio we see real estate "flippers" who buy bank-owned and other low price property, often at less than $10,000. Then without doing much to improve the properties, and via appraisal voodoo, they turn around and sell the houses for $50,000 - $100,000 to those desperate to get into home ownership. These unsophisticated buyers often end up in foreclosure and the hunt for a new set of suckers starts the process once more.

The blue nodes on the left are the owners of various Slavic Village properties in the early 2000s -- most are banks and other financial institutions. The flippers are the green nodes in the middle. The new home owners are the magenta colored nodes on the right. The flow of sales go left to right -- following the light gray links. A sells to B : A --> B.

From initial sale to foreclosure usually takes anywhere from 12 to 36 months. This process was repeated again and again with blinding speed during the period of 2003 to 2007. Most of the flippers and their collaborators have now been indicted by the Cuyahoga County Prosecutor and will face trial in October 2009.



All data was gathered from public records of real estate sales in the Slavic Village neighborhood in Cleveland and from indictments on the prosecutor's web site.

Finding the Flippers

The recent mortgage meltdown had many players in many places. The investment banks on Wall Street needed large amounts of sub-prime loans to package into investment vehicles. To satisfy this need, they found plenty of help in most of America's major cities. Some local banks, brokers and appraisers were more than happy to generate an almost unlimited supply new mortgages. The generals on Wall Street had boots on the ground on Main Street.

One of the bloodiest battles was fought in Cleveland, in the Slavic Village neighborhood. Today the streets of Slavic Village show the scars of the battle -- destroyed homes, destroyed lives and vacant lots. From 2003 to 2007 houses were bought and sold at an alarming rate in this working class neighborhood. House were bought cheap and almost immediately sold at multiples of their true worth -- this is commonly called flipping. Most new owners ended up with with sub-prime mortgages that put them on the fast track to foreclosure. A local real estate gang had emerged, and was partnering with mortgage bankers in California. They had the home sales process covered -- seller, broker, appraiser, banker, buyer -- all lined up to feed Wall Street a never ending supply of sub-prime mortgages.

Anthony Brancatelli was the local Cleveland city councilman in Slavic Village. He could not believe what was going on in his neighborhood. He started tracking real estate activity in his neighborhood via a spreadsheet -- the same names and the same companies kept popping up. With the help of public records, soon Brancatelli and colleagues had the details on hundreds of real estate transactions which were compiled in a report by The Slavic Village Vacant and Abandoned Property Task Force.

Brancatelli's spreadsheet looks like this...


The network of sales transactions revealed in the spreadsheet are mapped below. A green line with an arrow shows "who sold to whom": seller --> buyer. The nodes/buyers hi-lited in pink ended up in foreclosure. As you can see, most buyers in these transactions ended up in foreclosure. Nodes in black are organizations, other nodes are individuals. We removed all names from all maps.


Digging deeper into the spreadsheet and into public records, it was revealed who had business ties with whom. The network map below shows a grey link between two nodes if they show a business tie -- working together, owning property together, appear on LLC documents together, etc. The nodes hi-lited in blue where indicted in the first wave in the autumn of 2008. The nodes hi-lited in green were just indicted in 2009. All of the blue and green hi-lited nodes in this network map were big sellers of real estate in the first map [they had many outgoing arrows].

It is easy to see who will be swept up in the next wave of indictments, or who will be on the witness list in the upcoming trials.


Sadly, every major city probably has maps likes this waiting to be revealed. The mortgage meltdown did not just happen on Wall Street. It was a alliance between Wall Street and real estate speculators on Main Street. Cleveland has started rounding up these crooks thanks to efforts of local neighborhood residents and elected officials like Anthony Brancatelli.

Connecting Yourself to a New Job

This morning I appeared on WCPN - 90.3 FM, the Cleveland NPR radio station, on "The Sound of Ideas" with Dan Moulthrop. The program was about searching for a job when you are over 50 years old. Listen to the MP3 here.

When is the best time to plant a tree?
20 years ago.

When is the next best time to plant a tree?
Today!

Chinese Proverb

What is true for trees, is true for networks -- build your network before you need it!

It is best to have been building and expanding your strategic personal network for all of your professional life. Unfortunately, most people don't come to that realization until they are let go from their current job.

Most people have small, dense networks composed mostly of their immediate on-the-job colleagues, friends and family. These networks are the first resource of the newly furloughed employee. Asking around, the job-seeker finds that immediate contacts often do not have much more job information than the job searcher has -- they are all in the same network neighborhood where everyone knows what everyone else knows at about the same time.


Once the job seeker exhausts the obvious job openings that s/he and their immediate contacts are aware of, they become stuck. What to do next? The common advice is send out or post resumes on-line, attend job fairs and start "networking". The first two suggestions get the job seeker onto the overcrowded freeway to the HR office. In today's recession, this route is a clogged artery with little or no movement -- time to get out of this traffic jam and try an alternate path.

The next suggestion -- "networking" -- sounds good, but is often approached wrong. Networking is commonly defined as quickly connecting with many people -- focus on quantity over quality -- sometimes mockingly called schmoozing. Building strategic connections is much different than just "networking" -- you build trusted relationships that bring you information and access that you currently don't have in your small circle of friends and colleagues. Quality trusted ties are like the trees planted many years ago. Quality trusted ties develop when people work on something together -- they don't develop over a handshake at a conference, a quick conversation over coffee or a speed interview at a job fair.

Networking may get you many new business cards, but are these people willing and able to introduce you to the hiring manager [the route around the clogged freeway]? If I just met you at a conference, or you called me out of the blue "to network", am I going to risk my professional reputation to introduce you to my boss or trusted colleague? Probably not. Yet, if you are introduced to me by a trusted friend, colleague or peer then I will listen and we will both benefit. Better yet, if we work on a volunteer project together, I see you "in action" and we bond -- I feel confident in recommending you.

Once you exhaust your inner circle of people who can make introductions, what do you do? Two things: 1) re-activate trusted ties from the past that are now dormant and 2) build new trusted ties via volunteering and part-time work.

Everyone has dormant connections that can be re-activated. Many people are now getting on Facebook and LinkedIn and re-connecting with former colleagues and college chums. Do so, but be careful. Do not re-connect with a transaction in your back pocket -- "Hi, nice to to hear from you again, do you know of any jobs?" I have a former colleague who re-connects with me every 5-7 years -- but he does so only when he is in the job market! He expects a connection, but is not eager to offer one of his own. Needless to say, he does not get far. Once you re-connect with one or two trusted ties ask them if they have remained in contact with others from your old social circle. You want to be expanding/re-activating your current network out 1 and 2 steps -- your contacts and hopefully their contacts. This will help you reach people with information about jobs you have not heard of yet.

A friend of mine, a job-seeking HR executive in Chicago, has done an amazing job of building her strategic network in the last year. She has dozens of new connections she built in prolonged interactions. She has volunteered on several projects in her field and also sits on several advisory boards. She has helped organize several local HR conferences and meetings and therefore has face-to-face work experience with a totally new cadre of colleagues. She now has a handful of strong trusted ties that she did not have last year. They have seen her in action, they like her work, they trust her, they give out their personal cell phone numbers to be references for her! Like a tree establishing a root system, it has taken her a while to grow this strategic network, but it is now vibrant and ready to provide her with many opportunities.

In addition to job offers and business opportunities, a wide strategic network also provides other benefits. Health and happiness! When I talked to my HR colleague in Chicago this week, she did not come across as a person that had been out of work for a while. She was very upbeat and full of energy -- which comes across in an interview! She was very positive because her network was growing and bringing results. She was meeting new people, sharpening her skills and learning new behaviors -- she was very positive about her future. More and more research is pointing to the health benefits of building social networks. Employers like to hire positive, high energy people.

Out of work? Form new ties -- not casual connections, but collaborative caring connections, built up over time. They will bring you a variety of rewards. Also, when you start your new job, do not stop your network building. Keep expanding your network, make new connections in new places. Keep growing that tree, you planted, with wide-reaching branches.

"Only connect!
Live in fragments no longer."

Howard's End
E. M. Forster

UPDATE: The friend mentioned above DID get the job with glowing references from the strong ties she had formed working on various local HR conferences and events in Chicago. She built a real network and it paid off!

Network Structure of Swine Flu Pandemic

The Swine Flu has been in the news during April 2009. Initially it spread amongst pigs, and then made the jump to humans that came in contact with the contagious pigs. From the early data, this appears to have happened in Mexico.

We use the social network analysis software, InFlow, to illustrate the spread of the contagion. Below is a social network map of the connections between employees in a large organization [data is real, names have been hidden]. A grey line indicates face-to-face [F2F] contact between two employees.


Now, one of the employees visits relatives in Mexico, who live on a farm and have pigs. The swine flu virus infects this employee, whose immune system has not been previously exposed to Swine Influenza A -- H1N1. The link of that infection is mapped below. The contagious pig is represented by the pink node. The disease transmission vector is represented by the green link.


If there is no human-to-human transmission of the swine flu virus then the disease stops here. One person sick, no contacts infected. Unfortunately, the CDC now acknowledges that transmission of this virus from person-to-person is possible -- one patient visited Mexico, came home sick, and passed the virus to another household contact who had not accompanied him on the trip.

Now the contact network at this workplace becomes a disease transmission network, as is common with airborne contagions. Also, this workplace network overlaps with other networks -- each employee goes home to a family/neighborhood/social network which also include F2F contact. As the virus spreads in the workplace, it will also be transmitted to other networks connected to the workplace network by common members.

The sick employee may still come to work initially and via coughing and sneezing start to spread the virus to others in the same space/location. The first wave of disease transmission is mapped below. We now show only the disease transmission links in green and hi-lite each node [yellow] that has been infected by the virus. For this simple example we are assuming a 100% infection rate [higher than usual] -- if someone coughs or sneezes in your presence, you will catch the flu after the normal incubation period, typically 1 to 3 days.


The map below shows how the virus spreads via person-to-person contact. Even if the original infected individuals are no longer at work, the density of the network, with multiple paths between individuals, ensures that many will be exposed.



The virus spreads because infectious individuals constantly come in contact with those who have not been exposed. Because of local density in a typical human network, a healthy person can be exposed to multiple sick individuals, thus increasing the odds of transmission. We can watch the contagion spread to the rest of the population, but in most cases some action would be taken once a significant portion of a local population becomes ill. Either government authorities or the employer will step in to isolate the sick from the healthy.

Ironically, the network structure that enhances the transmission of good contagions -- such as ideas, solutions, and knowledge, can also transmit bad contagions such as disease and fear. When the network is transporting ideas and knowledge we want to decrease distance between individuals. When the network starts to transmit disease we want to increase distance and fragmentation in the network to isolate the virus and slow/stop the spread.

For a deeper dive on social network analysis and contact tracing applied to public health issues see this CDC paper.

Be careful how you connect in the next few months!

Operation Air Ball

The Cuyahoga County corruption scandal in NE Ohio continues forward with tentacles reaching into various suburbs surrounding Cleveland. The FBI has named their project "Operation Air Ball" -- no one quite knows why this basketball term, for a very bad shot, was chosen.

A social network analysis map of the organizations and businesses that have been searched by the FBI/IRS team is shown above. Two organizations are connected by a green link if they have done direct business with each other according to the FBI/IRS subpoenas. If a person connects two organizations, by being associated with each one, that relationship is not shown. Later, we will have a map of individuals and organizations with all of the interconnections.

The data to create the map was gathered from reporting on the scandal by The Cleveland Plain Dealer and WKYC News. No guilt is implied, or assumed, via appearance on the map.

As more data becomes available we will add to this map and also create other maps so that interested parties can track this complex case as it evolves. A citizen's effort called Map the Mess is also tracking this investigation, and "connecting the dots" in the news stories.

For more insight into how these maps are done, read how we first mapped and analyzed the 9-11 hijackers.

Update: network map current as of 04/01/09

Contagion amongst Banks

This week's PBS Frontline show was fascinating. They discussed the financial meltdown and how it was exacerbated by the massive intra-connectivity of the banking system.

Frontline focused on the trade-offs between "moral hazard" -- punishing the bad guys for bad behavior, and "systemic risk" -- allowing the bad guys to fail and effect the rest of the interconnected system. The main contagion under discussion were the investments created by Bear Stearns, Lehman Brothers -- packaging up sub-prime and other mortgages into mortgage-backed securities which were then sold to other banks and investors.

Using social network analysis, let's take a look at how a contagion spreads through a connected system. Below, is a small-world network that models the interconnected banking ecosystem. The red nodes represent banks, while the grey links represent who may be doing business with whom. The arrows represent the flow of assets.

We will look at three nodes/banks and the effect they have on the rest of the system. The nodes/banks are labeled: A, B, and C. We chose to examine these nodes because they are in different parts of the network. A is in the thick of things, in the dense center cluster. B is on the periphery of that dense cluster, and C is very lightly connected node at the very edge of the system.


First we look at the best connected node, A -- deep in the dense part of the network. Suppose Bank A is selling toxic assets it has packaged as investments. We ask our social network analysis software to show the immediate connections of node A -- it's direct business partners -- those who are buying the toxic assets. The nodes that show up in yellow, with the red border, below are one step away from the bank selling toxic assets -- they do business directly with the infected bank. We now see that a portion of the banking network is infected -- yellow nodes are infected, solid red nodes are not.


Next we move out two steps from the infectious bank -- the yellow nodes now show both the direct and indirect business partners of the infected bank -- we notice how quickly the contagion spreads as the mortgage-backed securities are packaged and re-packaged and sold and re-sold. Now we have more yellow/infected nodes than red/non-infected nodes -- the system has tipped.


Now we move out three steps -- 3 degrees of separation -- from the infectious bank. We see that just about the whole ecosystem is now infected with some level of toxic assets. With all of re-packaging and re-selling of the securities no one really knows how much everyone is infected, but every yellow node is infected to some degree.


As we expected, the well connected node in the thick of things spread the toxicity quickly to the rest of the system. Do the other nodes also have the ability to poison the well from where they sit?

Next, we look at the bank on the periphery of the dense cluster -- node B, on the left side of the network. How fast will it's contagion spread? At one step, the spread is mostly local.


At two steps there is an quick distribution of the contagion, including our original highly connected node in the dense middle. Once the highly connected node is infected we know the rest of the story from above.


At three steps away from B a majority of the network is infected. We see that a bank on the periphery can also be devastating to any system it is embedded in.


Finally we look at the bank that is barely connected to the system, node C. What effect will it have if it sells toxic assets into the inter-bank network? The initial transactions only infect a few nodes that are also on the edges of the network.


At two steps, the contagion has touched the dense central cluster.


At three steps from Bank C, a majority of the network is infected by the toxic asset. The "outsider" was able to infect the rest of the network -- it happened more slowly, but as investments were re-packaged and deals were made the contagion moved forward.


There is good news and bad news about slow-moving contagions. The good news is they can be spotted and stopped before they do too much damage. The bad news is they are often ignored early on, because they have not done enough damage to pop up on anyone's radar -- so they spread stealthily.

The key decisions the prior administration needed to make was to decide whether to follow the moral hazard argument or the systemic risk argument. With Bear Stearns they chose systemic risk -- they felt Bear Stearns was too connected to allow to fail. With Lehman Brothers they chose moral hazard -- they did not think Lehman was connected enough to cause systemic risk. They were wrong. As we saw above, a connected system is very vulnerable to any node feeding contagions into it.

Now that the banking system is infected with toxic assets, none of the banks want to trade with each other. They don't know what they are getting from their trading partners. No one trusts each other. The financial meltdown has led to a freeze-up of trust and activity. It is like all of the old links went away and you have disconnected nodes staring at each other... too scared to move.

Social Network Analysis Workshop

Escape the snowy North and come learn something new in sunny San Diego!

Valdis Krebs will be presenting a 1/2 day workshop on practical applications of social network analysis [SNA] at the upcoming Sunbelt Social Network Conference sponsored by INSNA -- International Network for Social Network Analysis.

This workshop will be on the morning of March 11th at the Bahia Hotel @ Mission Beach in San Diego, California. The Sunbelt conference will run until Sunday, March 15th in the same Hotel.

The hands-on workshop will feature a quick overview of social network analysis as applied to organizations and communities. You will get a chance to use social network analysis software to explore a simple data set. Whether you are a consultant, analyst, manager, activist, student, professor, or journalist you will learn how to apply this useful methodology with clients and customers.

Sunbelt is a mostly academic conference but is attended by more and more practitioners every year. Valdis and Erin Kenneally [both practitioners] will give a presentation during the regular conference on Analyzing Networks of Corruption.

Madoff Feeder Funds

Yesterday a list of the victims of the alleged Bernie Madoff ponzi scheme were released -- 162 pages of 4 point type listing thousands of names and addresses.

What was not released were the social networks that connected these people to Mr. Madoff -- who made the introduction, who closed the triangle to turpitude? This, after all, was a crime based on inclusion and exclusion in select social networks. No one wanted to be excluded from this great deal with one of the wizards of Wall Street -- yearly double digit returns, guaranteed. They used their connections to gain inclusion into the money flow network. And for a while, that inclusion felt good.

Madoff apparently worked with multiple "feeders" into his investment system. A wide network of individuals and funds were set up to pass money to Madoff. Most investors in these funds did not realize all of their money was going to just one place -- a place that is turning out to be one big hole. Inclusion seemed to be the prize, but it ended up being the trap.

Below is an attempt to keep up with this rapidly developing story and map the investors into Madoff's funds. Every day new players and their connections are revealed. The thousands of victims on the 162 page list probably trusted an intermediary institution or feeder fund with their money.


If you would like an interactive map of the above, you can find one on my orgnet.com web site. On the interactive network map you can double-click on any node in the network and get the latest news of that node's involvement with Madoff.

All data for these maps was gathered from news stories and court documents found on major media web sites.

Mapping Political Corruption

Cleveland and NE Ohio have a corruption scandal brewing. The local newspaper, The Plain Dealer, is reporting the corruption story while at the same time it is in the process of downsizing. The PD has done a very good job of reporting the the ongoing investigation -- a team of almost a dozen reporters have been tasked to track the developing story.

Below is an early effort to map the corruption mess by a group of citizen journalists. This map reveals a process we see often in today's corruption cases -- the indirect quid pro quo. An indirect quid pro quo moves the influencer away from the final target of influence, via long paths of multiple intermediaries.


The indirect quid pro quo results in plausible deniability for the influencer because there is no direct connection to the target of influence. The red arrows show both flow of benefit and flow of influence. The data to create this map is taken directly from this published Plain Dealer article.

Triangles on Twitter

We often talk about closing triangles and making introductions as a way to build resilient networks through network weaving.

Here is an example of closing triangles via Twitter. Track the triangle closing process from my Twitter log above -- oldest tweet on bottom. The blank space in the tweet log was from another person I am following that had nothing to do with the closing of the triangle. Starting at the bottom of the above pic...

1) I follow John Robb on Twitter and he tweets about a book he is reading
2) I re-tweet his post so that those who follow me on Twitter can learn about the book.
3) June, who is following me, sees the re-tweet and aims her tweet at John [using @johnrobb] stating she has read the book and found it useful.

Two people that I have known, but did not know each other, can now be connected. They connect by seeing [via Twitter] their mutual interest in a book and in an idea. Maybe June and John can now talk about "resilient communities" and their experiences with them?

Since June and John have some similar interests, yet come from different communities and contexts, we have another example of...

"Connect on your similarities and profit from your differences"

Pop!Tech 2008

You know my old saying...

"Connect on your similarities and profit from your differences"

One of the best places to practice that -- if you are a progressive, technical, social, global/local thinker is at the annual Pop!Tech conference held in Camden, Maine every October. Can't remember how many people I met -- many more than the biz cards I collected. They were ALL interesting, if not outright fascinating, each in their own way!

Andrew Zolli, who is the conference curator, is a master network weaver -- connecting others through placement in the program or F2F introductions. You want to connect to Andrew, he will close many triangles for you.

THE conference for connecting -- Pop!Tech.

Power in Economic Networks

The colder it gets the more power they have.

Who? Those that control the flow of natural gas used to heat homes, schools and other buildings in the European Union. Currently the two key players in the gas pipeline network that supplies Europe are in a disagreement over pricing, access and many other things. Russia has the natural gas, but the Ukraine is the gas transport gatekeeper on the steps of Europe. Details of the economic tug-of-war are in several places, including one of my favorite blogs.

The golden rule of networks is the same as the golden rule of Real Estate -- location, location, location. Find a good location, and you may have some power over the network. End up in a bad location in the network and you may get very cold while you helplessly watch others maneuver.

Below is a network map of the gas flow from Russia, and it's surrounding countries, to Europe. Countries are the green squares in the network, major gas fields are the blue circles. The major players in this battle are Russia, the red node, Ukraine, the yellow node, and Germany, the black node. These important nodes in the network were found using a metric from social network analysis called betweenness. Naturally, Russia is the most central player in the network, Ukraine is close behind, and Germany is locally central within Europe, and a distant third.


Russia is well aware of its dependence on Ukraine for the transport of gas to Europe. Russia would rather avoid that dependency. They have a plan. With Germany, the key node in Europe, Russia plans to build a pipeline that will route around Ukraine, and Belarus [in case they begin to exploit their location], and go straight to Germany. This Baltic Bypass will go under the Baltic Sea. This new pipeline is indicated by the red link in the map below -- though it will not be a straight line in the real world. The proposed pipeline will leave Russia between Estonia and Finland and run down the Baltic Sea past Latvia and Lithuania to the German coast.


Applying our centrality metrics again, this time we see a dramatic change. Russia, is still the most central player, but now Germany is second and Kazakhstan is third, leaving the Ukraine a distant fourth -- in a much weaker position. One new link changes the competitive landscape. In the connected world we will see more jostling for better location in the network -- with counter-measures coming quickly. The networked chess board?

Do you know your network landscape and who is adding links or taking them away? A white paper on how power changes in a network when link patterns are altered is available at orgnet.com.

May you be well located in the New Year!

UPDATE: An interactive map of the current pipeline structure.

So many people, So little time

There are many interesting discussions happening on Twitter in the last few weeks. I have been paying attention to the conversations about how to measure social media influence/rank/authority. Many people trying many metrics. All of the current measures seem to have their issues... one gives too many high scores, another spits out way too many around the median, and still others are easy "to game."

IMHO, the best metric so far is Retweet Rank -- it is not perfect, nor complete, but it gets at a key aspect of Twitter -- what is interesting, what are people paying attention to, what is useful and who is sharing all of that. If someone re-tweets what you posted/tweeted then that is a vote of attention/quality -- if many people re-tweet you, or the re-tweet the person that already re-tweeted you, then better yet! In this sense Retweet Rank follows the example of Google's very successful PageRank algorithm -- people point to web content they find interesting/useful/valuable.

In a recent exchange someone asked me, "Why do you follow so few people on Twitter, yet many people seem to follow you?" I answered, "Simple, it takes effort and time to follow people, but much less time & effort to have many people follow me." This reveals a typical constraint in all of our social networks -- we only have so much time/energy/attention to devote to people in our lives, we cannot be connected to everyone. Even on the internet we must choose where we pay attention.

The diagram below shows an individual's social network. The person in the middle [red node] has a set [green nodes] of friends/family/colleagues or people they follow on Twitter.

Each of those friends/colleagues/follows also has friends/colleagues/follows. We build a fractal-like network map -- each green node above has a network map like the red node above -- self-similarity through all levels. The 2 step network of the red node above may look like the diagram below -- a social spore? Click on picture below to see detailed structure.


Each of the social circles seem to be isolated from each other. Looking at this picture of a person's social network, we think we need to follow at least one person in each social circle/cluster/community to know what is being said in that group.

But the picture above is misleading -- it forgets one important aspect of all social networks. Friends of your friends are often friends. Colleagues of your colleagues are often colleagues. Those ties are missing from the simple picture above. The map below includes the links that exist between and amongst friends and colleagues. Click on picture below to see detailed structure.


Our software finds the emergent patterns in the data, but the massive interconnectivity between friends and colleagues does not leave us with a pretty picture like the simple social spore above. Click on picture below to see detailed structure.


So, if many of the social circles above are already interconnected do I have follow an individual in each social circle/community on Twitter? Probably not. The trick is to find the people that reach many social circles and follow them. Of course, we need to find more than the minimum of people to follow -- you want some redundancy in your network so that there are multiple paths to places of interest for you. Finding these key nodes is what social network analysis is all about.

And this is why I follow so few people on Twitter! For the time invested, I want maximum return. I use the redundancy of connections, between the many social circles I am interested in, to my advantage. I follow a select group of people that give me the same access as following someone in every group. Follow the few to reach the many!

Because I have chosen them carefully, I want to actually read the tweets of the people I follow. A small part of my "following network" is always in churn, but the number of people I follow on Twitter never exceeds 100 [currently I follow about 70]. Those who follow thousands of people readily admit that they can not read the fire hose of tweets they get every day.

Strategically I am building a small, yet efficient, group that reaches out into the many diverse information pools I am interested in. I know I am finding good people to follow on Twitter by the number of great exchanges that emerge on many topics. Think before you follow, use your time and ties wisely!

UPDATE #1: Looks like Stowe Boyd advises to keep "Following" count >= 100. Hat tip to Robert Patterson. I will usually add new people to follow and then may keep them, or substitute them for someone else after a week or so. I tend to have a core of 50 people that do not change much, and then another ring of 20-30 that churn. People that stay in this later group eventually become part of the core -- which grows slowly over time.

UPDATE #2: Another reason not to auto-follow people was revealed by the recent Twitter SPAM and HACK attacks. People were spammed via the "direct message" [a.k.a. "d m"] protocol in Twitter. A direct message in Twitter is a private correspondence between two people on Twitter that are following each other. A dm is like a short private email. You can only get a dm from people you follow, and if you auto-follow, chances are you will be spammed. Don't be a promiscuous follower, practice safe following!

Password theft is going on in Twitter. This is how people are breaking into Twitter accounts. What may be happening is password harvesting via the many Twitter rank/authority/influence applications that are so popular now. Many ask for your Twitter username AND password. I avoid those apps and just visit apps like Retweet Rank that only ask for your public user name and not your private password.

Team Chemistry Wins Again

The University of Maryland Terrapins have won the Men's College Cup [NCAA Division I championship] again -- second time since 2005.

What makes this team special? Lot's of individual talent, for sure. But the key is connected talent -- team chemistry.

This championship soccer program has been doing social network analysis [SNA] since 2004. The coach's brother -- Vancho Cirovski -- learned the SNA process, as a client of mine, while he was an HR executive. Vancho first experimented with SNA when his brother's talented team was struggling in 2004. Among other things, the SNA process allowed the brothers to see who the natural/emergent leaders were on the team. SNA revealed both the on-field and off-field leaders.

This year, the SNA revealed three emergent leaders on the team -- all were named co-captains at the beginning of the season. We will share more details of the social network analysis on my orgnet.com site after the celebrations are over.

The team's use of social network analysis in prior seasons was written up by Business Week in this 2006 article: Game Plan: First Find The Leaders

UPDATE: Chemistry in Cleveland!

From NBA.com...

[Coach] Brown has praised the cohesiveness of the current group.

"Our guys understand that we're a defensive team," he said. "That's our identity, but the biggest thing is just the chemistry that the group has amongst one another. They like each other a ton and they want to play for one another, which makes it fun."

Social Life of Routers

Routers also have "friends", and their own "Facebook" -- routing tables that tell each router who it is connected to [no pictures of drunk routers though].

Eight years ago I wrote a technical paper about applying social network analysis to designing better computer networks. It is still one of the most downloaded PDFs from my web site, so it must still be useful. I wrote this paper after discussions with Guy Hagen and Ed Vielmetti, who connected me to the editor of Cisco's Internet Protocol Journal, Olé Jacobsen. Ed closes at lot of triangles!

Thanks for the update

Being a student of networks and information flow, a story from this morning's newspaper struck a chord. Information does not always flow in a direct or timely manner.

Having been a geeky kid in high school, who was good in math and science, the story was instantly recognizable, and I erupted into laughter -- the kind that recognizes an irony in life.

Dr. Martin Chalfie wins the 2008 Nobel Prize for Chemistry, for his work on green fluorescent proteins that help scientists study disease. With this prize, and the recognition it brings, Dr. Chalfie's network starts to change. People want to be associated with fame & recognition, even if they do not get it themselves. Many contacts came in to Dr. Chalfie, some new, some old. It was an old dormant tie from high school that forms the basis of the story.

One woman from his high school days in Skokie, Ill., told him, “You know, several of my friends had crushes on you."

I wrote her back to say, "Why are telling me this now? Back then, it would have been a very useful piece of information.”

Content is important in information flows, but equally important is context. A key component in context is timing. Right timing = useful & actionable, poor timing = missed opportunity, frustration, or outright laughter.

Full story in NY Times.

Team of Rivals: Weaving a Diverse Network

Congratulations Mr. Community Organizer... you beat them with the strategy they mocked!

Recently, I read an excellent book by Doris Kearns Goodwin -- Team of Rivals: The Political Genius of Abraham Lincoln.

In order to deal with a divided nation, Abraham Lincoln chose his cabinet from the best minds available. He ended up with a cabinet composed of mostly his rivals for the 1861-64 presidency. He chose these men for their abilities and experience. Lincoln knew the problems he faced were too much for one person. He knew he needed a team of experts -- all more capable than him in their specialities.

Lincoln was a master network weaver in not only creating his team, but also managing them. A diverse team is difficult to manage, but usually produces better results than a team of like-thinkers. The key to Lincoln's diverse team was different thinking and different expertise and different styles. Yet, by appearance they were very similar -- all old white men. Same packaging, but different attributes.

Today's corporate world is full of apparently diverse individuals -- men, women, whites, blacks, asians, latinos, christians, jews, muslims, gay and straight. Yet, most corporations reward similar thinking -- which does not bring the rewards that diversity promises. We have organizations full of people that look different, but think the same. Everyone should read Team of Rivals to see how to mix, match and manage different skills, styles and abilities for maximum effectiveness.

We focus on Barack Obama's ethnicity -- but that is not why he won. It is his message, his vision, his leadership. 150 years ago, a tall skinny guy from Illinois focused on connecting a severely divided nation. Now, another tall skinny guy from Illinois faces a differently divided nation and needs the best team possible to move this country forward. I was glad to hear that Team of Rivals is one of Obama's favorite books. He will need to apply it's lessons learned to have an effective presidency in these tough times.

In the connected world, we need a connected leader.

Complete Polarization

As both presidential campaigns sprint toward the finish line I took one more look at the political books being bought in October 2008 and the patterns they created.

The arrows in the network map above show which books were "also bought" together. A-->B shows that customers who bought A, also bought B. Click on the map above for a larger view.

A few surprising patterns...

• unlike in previous maps, there are no bridging books between the red and blue clusters -- the two parties are totally separated! This reflects the immense polarization and animosity we currently see in campaign rallies on both sides.
  
• the "key book" of community organizers -- Rules for Radicals -- was being bought by the right-wing! It was being purchased along with several anti-Obama books. Is the Right trying to figure out why Obama's campaign, based on community organizing principals, is so successful? Maybe articles like this are driving the curious red to read normally blue books?
  
• those buying positive books about Obama, are not buying other political books. Are they interested in the candidate, but not politics in general?
  
• there are no books about McCain or Biden that made the Amazon cut-off for "most popular political books." The book about Palin -- Sarah -- is the only popular book about the Republican team.
  
• the Right focus on fewer books to get their message across. The map does not reflect volume of books sold. It is possible that the Right buy more volume of fewer books.
  

See previous views of political book patterns in 2004, and 2008.

Data Mining for Networks of Terrorists

This week the Department of Homeland Security received the results from a study by the National Research Council [full report] that the DHS funded. The study's conclusion: data mining for terrorists does not work and it invades the privacy of innocent citizens. Searching for the terrorist needle in the haystack of phone-calls and emails is counter-productive.

I told you so... here, here, here, here, and here.

However, if you start with a known suspect or two, you can roll up the rest of the network with normal surveillance techniques. Rather than dig through millions of records looking for that unknown terrorist pattern, give the phone company the numbers of known suspects/terrorists and have them return the 2-step network neighborhood of each number -- now you can see the terror suspect's extended social graph. This approach with social network analysis also uncloaks street gangs and criminal networks.

UPDATE: ABC News has more on surveillance of US Citizens abroad.

Political Patterns on Amazon

This week, I am blogging on one of the Amazon blogs -- Omnivoracious.

Multiple people are posting about various approaches on how book purchases relate to the upcoming 2008 US presidential election. I am grateful to be included with such experts as John Zogby, Bill Bishop, and Andrew Gelman. Each of us has a different approach for how to mine Amazon data for interesting insights.

Here are my two current posts... intro & book maps.

Enjoy!

Non-Obvious Ties

How many NOTs in your network? [NOT = Non-Obvious Tie]

You probably can't answer that, because the connections are...
n o n - o b v i o u s .

Ties/links/connections/relationships that are not obvious to me may be obvious to someone else, and vice versa. Unfortunately, the knowledge of those ties may not be as valuable to those those who know, than to those who do not know.

Confused? Let me share a few stories...

This afternoon I was looking through the access logs to my business web site. I saw some interesting NOTs. Two *.mil organizations were visiting certain pages. Would my friends at Booz-Allen-Hamilton would find that information of great value? BAH sells products and services to DoD clients. The BAH rainmakers would love to know what military branch X and Y are interested in and what search terms they used, and what pages they spent a long time on.

Then I noticed visitors from the Dark Web [web sites that support/idolize Jihad]. I wondered... wouldn't the military folks, that visited just an hour before, like to see what the jihadi supporters were looking at, and what referrer pages and search terms they used?

Finally a third NOT, all in one quick browse of the logs. Wouldn't the Oracle business intelligence folks like to know what SAP employees were looking at, and vice versa?

My web site is not that different from thousands of other business web sites that are browsed each day by a diverse mix of concurrent visitors. If only visitor X knew that visitor Y was there and what they were looking at. Maybe a few days later visitor Z arrives and produces the same clickstream as visitor X -- what does that say about the two visitors?

Our choices reveal who we are. Our search paths give insight into who we are not... yet.

Even though though we don't know who each of these visitors are [the actual people representing their organization], their behavior reveals much about what is important in their organization and what they are trying to learn. Just like the networks of Amazon purchase data reveal interesting political patterns without revealing who the actual purchasers are, these "choice & search" networks reveal much about the organizations our individually unknown visitors are from.

Finally, a NOT story with a happy ending.

A blogger friend of mine was being stalked by someone who took great umbrage to one of the posts on the blog. The stalker assumed a Jane Doe identity and started to leave increasingly abusive comments. By checking the blog logs my friend saw the IP address of the abuser and saw that they were spending a lot of time on the site. They were waiting for the blogger to answer one of the abusive comments or for a friend of the blogger to leave a positive comment that they could pounce on.

The stalker was using his employer's network. Yes, she was a he, a quick domain look up revealed what company he worked for. The company sold financial products and services to consumers. My friend thought they would guard their reputation vigorously. My friend contacted their media relations department and explained the situation and provided them the IP address from which the comments were coming. Soon the company's director of IT Security called and explained how seriously they were taking this misuse of their network. Within a day, the IP address and the abuser's fake Jane Doe GMail address were tracked to a PC within a company branch office. Both HR and I/T approached the abuser and basically read him the riot act. He quickly admitted his guilt and pleaded for forgiveness. No details, other than the above, were provided by the company. As a former HR person, I suspect he will be very closely watched and most likely terminated at the next display of similar behavior. His opportunities for promotion and advancement are now severely limited. Dumb guy.

A similar process, to the above, is currently being used to trace the hacker who broke into Sarah Palin's YahooMail account(s). Many people think they are anonymous and invisible on the internet. Not so -- NOTs will quickly reveal what you are after, where you came from and finally, who you are.

We confirm, You conform

We have seen how obesity and smoking are affected by the network around an individual. Alas, it also works for crime and terror. From the BBC report on how people become terrorists:

The picture that emerges is of largely intelligent people finding direction in the networks of associates they keep.

"The work on pathways into terrorism indicates that it comes out of a social process; it comes out of a series of contacts that terrorists have with other individuals," Professor Canter told BBC News.

"At the broader level, everything has to be done to undermine the idea that individuals think of themselves solely in terms of any particular group of sub-group - be that fundamental Muslims or supporters of a football club . Once people only think of themselves in those terms, then that sets the seeds for conflict."

Re-read that last paragraph above.

Any group that isolates itself, by just focusing on itself, sows the seeds of conflict with the rest of society. Groups isolated from the rest of society are not automatically terrorists [look at the Amish], but they are places where confirmation [what we all think is correct] and conformation [you must not think differently than us] are oppressive forces acting on group members.

We confirm, you conform are the unspoken rules in any isolated group, whether they be criminals, terrorists, religious zealots or those overly fanatical about their political party or sports team.

Below are some of the close internal ties of the 9/11 hijackers. Included in their group were others who had already carried out acts of terror -- setting an example of behavior for the rest.

Political Book Buying Patterns

I'm surprised it took Amazon this long to exploit their own political book buying data. The Amazon maps go to where the power is -- state by state -- the Electoral College.

The Amazon maps indicate whether each state's residents purchased a larger number of red or blue books. Comparing my recent book network maps to the above pictured book volume map, seems to show that while the Left read a larger variety of books, in most states the Right buys greater quantities of a smaller set of books.

Some interesting questions remain...

• are book buyers influential with voters in their social network?
  
• how many voters does a typical political book reader reach/influence?
  
• are Amazon book buyers representative of the political book buying population?
  

Amazon clusters the political book sales data into 60 day slices. When you go back earlier in the year 2008, you see more blue or neutral shaded states. The most recent 60 day slice of 2008 [before and after the conventions] shows a blossoming of deep red. If polemics predict [no one knows for sure], and the election were today, then the latest Amazon political book data maps appear to indicate a President McCain in 2009.

Another nice feature that Amazon provides is to go back to 2004 and look at the political book buying patterns then. The most interesting change of patterns is between the map just before the 2004 election and the map immediately after the 2004 election.

Weekend Data Mining

During the Republican National Convention, John McCain's acceptance speech indicated that he was running against the current state of affairs in Washington DC. Will he be different than the current administration of George Bush? Is McCain a Republican of a different stripe? Will a McCain administration be different than a Bush administration? With only opinions and no data, we can argue all day and all night.

Maybe some data can help us see behind the rhetoric? One way to gain insight into possible future behavior is to look at who is donating to the campaign and hoping to influence a new administration.

I downloaded data of the top bundlers of donations for the 2000 and 2004 Bush campaigns and the 2008 McCain campaign. What's the overlap of donors between the Bush and McCain campaigns? Will the same people influence both campaigns/administrations? Or will it be starkly different groups? Or something in between?

From The Fix @ washingtonpost.com...

McCain's bundler program is built on the incredibly successful "Pioneer" and "Ranger" program built by George W. Bush in 2000 and perfected four years later. The most valuable individuals in a bundling program are not necessarily the wealthiest individuals but rather those individuals with the deepest Rolodexes and a willingness to ask and ask and ask.

Below is a map of those who donated to BOTH Bush and McCain. The campaigns are shown as the two red nodes on the left of the map. The green links show donations coming into the McCain 2008 campaign. The blue lines show donations coming into the Bush campaigns of 2000 and 2004. The 128 bundlers, who have contributed to both McCain and Bush, are shown in the arc on the right.



Most of McCain's 534 large bundled donations [76%] came from donors who did not donate to either of the Bush campaigns. Yet, this kernel of 128 bundlers keeps consistency across all three Republican campaigns in the 21st century.

Although the majority of McCain fundraisers were not Bush fundraisers, the Gang of 128 may not allow McCain to wander too far from the current philosophy and approach. If elected, McCain may be different than Bush, but he might not be that different.

Update: McCain 2008 Bundler List & Obama 2008 Bundler List

Know The Net

When you know the net you can quickly get to the information or resources you need in your local community.

So, the statements below about John McCain's vetting process for his VP candidate are puzzling. Did they not know how to scroll through the network via key access nodes [a.k.a. network weavers] or did they just not do it?

From the New York Times...

"They didn't speak to anyone in the Legislature, they didn't speak to anyone in the business community,"said Lyda Green, the state Senate president who lives in Wasilla, where Palin served as mayor.

Representative Gail Phillips, a Republican and former speaker of the state House, said the widespread surprise in Alaska when Palin was named to the ticket made her wonder how intensively the McCain campaign had vetted her.

"I started calling around and asking, and I have not been able to find one person that was called," Phillips said. "I called 30 to 40 people, political leaders, business leaders, community leaders. Not one of them had heard. Alaska is a very small community, we know people all over, but I haven't found anybody who was asked anything."

The current mayor of Wasilla, Dianne M. Keller, said she had not heard of any efforts to look into Ms. Palin's background. And Randy Ruedrich, the state Republican Party chairman, said he knew nothing of any vetting that had been conducted.

State Sen. Hollis French, a Democrat who is directing the ethics investigation, said that no one asked him about the allegations. "I heard not a word, not a single contact," he said.

In Athens, Ohio, one of the key community access nodes is June Holley -- she can probably connect you to any part of the community or economy, either directly, or in one or two introductions/steps. June is not the only community access node in Athens -- there are dozens. You don't have to find the best one -- many well connected nodes will work as a productive starting point in your journey through the net.

The people quoted above all seem to be key members of the Alaskan state government -- all probably within 2 steps of each other, and network neighbors of anyone you would want to talk to when checking references and reputations.

Was the vetting rushed, or did they really not know the net, and how to get the key information they needed?

How can 30-40 key political players not know what is going on?

Sounds like WMD 2.0 to me. Others call it toadyism.

What do you think?

UPDATE: They only checked within their own little clique -- those with broad reach to many cliques/clusters/groups were not contacted. Selective use of intelligence? Flawed patterns repeated?

From the Anchorage Daily News...

Thomas Van Flein, the Anchorage lawyer representing Palin and her office in the legislature's investigation into the firing of former Public Safety Commissioner Walt Monegan, said he spoke to several representatives from McCain before Palin's selection was announced Friday.

But Van Flein appears to be in a small minority in the vetting of Palin.

On Sunday, The Washington Post quoted McCain campaign manager Rick Davis as saying the FBI conducted a background check of Palin.

But Monday, the FBI told the Atlantic Monthly no such check took place.

If the newspapers can find key nodes in the net in just a few days, why couldn't the McCain campaign?

When a member of the echo chamber inquires within the echo chamber all s/he hears are the known echoes. And since the echoes appear to come from several places at once s/he believes that everyone thinks so, and therefore it must be the truth.

It's the Network, Stupid

It is amazing how many of our current problems come down to the realization that it's the network, the connectivity, that matters. In most situations we know how to fix and enhance the nodes in the network. The links, and their patterns and structure, are the hard problem.

We are making progress in alternative energy production, but we still fail at energy distribution. Windmills and solar energy collectors have made great progress -- we just can't get the energy from where the wind blows and the sun shines to where the great population centers are. To do that requires a well-designed power distribution grid. Many critics of the current grid describe it as "third world" in design, quality and capability. Today's New York Times describes the distribution problem well.



Above is a network map of a portion of the US electric grid. Life is great if you live in one of the densely connected clusters using electricity generated nearby. Things start to get real complicated if energy needs to transferred from one cluster to another cluster in grid. Distance destroys. Electricity does not flow like information or water or oil. It is not easy to direct, and much electricity is lost to heat when transferred over long distances. On the internet, 100 packets sent from Cleveland all arrive in New York wholly intact -- not so with a 100 MW of electricity generated in Cleveland and sold to NY. Even more electricity would be lost going to Miami, and forget about LA. It makes no sense to transfer electricity made in Cleveland to Los Angeles -- most of it would be lost during the trip.

Not only does physics get in the way, so do local interests. Then you have another power problem -- that of political power. Doing a social network analysis of the electric grid quickly points out key nodes and links that are highly between transfer points on the grid. They become gatekeepers/bottlenecks and either extract a toll for the transfer, or refuse transfer and require the buyer and seller to find a longer route to get from point of generation to point of consumption. And remember -- distance destroys.

Energy independence will take a lot more than just new technology at the point of generation. It will take the design of a much smarter network of distribution.

Web Site Social Network Analysis

Everyday I try to look at the Google Analytics [GA] data for my business web site -- orgnet.com -- and my blogs.

GA provides various export options of the data it presents to webmasters, so I have started to export some of the interesting views as CSV files which I then import into InFlow for social network analysis.

Using the GA data we see some interesting maps. Here are the 10,500+ web pages[red nodes] that point to a page on the orgnet.com site. Using InFlow's auto-arrange algorithm we see some simple clusters of our data. In this map the popular pages are self-evident.


What is more interesting is to see which pages have multiple incoming links to orgnet.com and which pages of ours they point to. These are our true fans, who really like our content. The map below show external pages/sites [red nodes] that have 3 or more links into orgnet.com -- the green nodes are the orgnet.com pages they link to. Again, I used the auto-arrange function to display an emergent ecosystem of our pages and the pages that support them. Green nodes [my web pages] that have similar incoming patterns arrange themselves near each other.


What would be nice is to map the two-step incoming links into my site. I am also investigating other mappings with the GA data -- further musings may be posted.

The Network Listener

Excellent new music from Brian Eno & David Byrne... free stream... enjoy!



Update: Ed V finds possible social network tracking code in embedded app... which of Valdis' friends enjoy this music enough to pass it on to their friends? See comments below.

Echoes Grow Louder

As we approach the 2008 U.S. presidential election, we notice new books focused on Barack Obama. A few of the books are negative on Obama and one is positive. The books do not not seem to be making much of a difference. The anti-Obama books are being read by those already predisposed against him and the pro-Obama book is solidly in the group supporting him. The din from both sides grows louder -- yes he is, no he isn't, yes he is, no he isn't ... Interestingly, NO currently popular political book, either pro or con, is written about the other candidate, McCain.

An interesting observation, from our social network analysis of political book buying data, is that none of the most influential books in the network of political bestsellers have anything to do with the upcoming election! What Happened, a look at the failings of the current presidency remains the most influential book. A close second in influence, The Post American World, a view into the rest of this 21st century, looks beyond immediate conditions to larger and longer term international trends.

Single Point of Failure

I can't tell you how many times I have seen this situation: company downsizes/rightsizes, becomes more "lean and mean", and then management scratches it's collective head when things start to fall apart.

Let's look at a simple example. Here is an organization before downsizing... two people are connected with a green link if they have a reporting relationship.


The emergent work flow is much different than the hierarchy. Here is how the work really gets done... two people are connected with a purple link if they actually work together.


Pruning boxes off the organizational hierarchy is easy when you only look at budget numbers, employment costs, and formal job descriptions. The Downsizing Task Force did not know the internal dynamics [emergent work flows, tacit knowledge exchanges, etc] of Andre's organization. Here is the organization after downsizing...


Fernando and Garth have been let go. "We have eliminated the high cost employees" management proudly proclaims! Maybe so, but they have also eliminated their own year-end bonus.

Here are the established work relationships now...


Of course the Downsizing Task Force is blind to this view of the organization, so they do not see obvious solutions like we do. Without social network analysis they will be scratching their heads for a while... what went wrong? ...what do we do?

Glad they made their RIF numbers!

Twitter Maps

When choosing a map, which do you prefer — pretty or useful?

In an ideal world I would take pretty useful, but forced to choose between the two I'll take useful.

Here are two social graphs taken from my Twitter following data.

The first map, by TweetWheel, is pretty, has nice colors, a simple and elegant interface, and a nice circular layout.



But what does it really tell me? What knowledge do I gain by looking at it?

The second map, by InFlow, is not as sexy, uses less color, and produces some complex emergent patterns.



Yet, this second map gives me more information -- it shows me emergent patterns in the data [both graphs use the same following data]. Using arrowheads, the InFlow map shows me who is following whom within the community. This network layout shows the emergent communities of interest found in the data. It tells me I am not just following one theme here.

Both maps have my node and my link data excluded for ease of readability. From the second map I see that I have chosen to follow people in three emergent groups [the gray nodes are just satellites of the purple group].

By looking at who is in the group I can easily label them. The top group [ClevOH] are my colleagues in various economic development projects in Cleveland and NE Ohio. The middle group I labeled the Digerati. This is a dense group with most members following most others within the group. I see many redundant links here -- I could stop following several of these folks and probably not miss much -- since they are mostly following each other and probably aware of the same information. This group has a few satellites -- they connect to only one or two nodes in the group and therefore are not full members.

The bottom group is well connected to the Digerati, but they do have a clustering of their own. These are well known consultants in Knowledge Management, Social Networks, Organization Development and Management. Once the satellites on the right see this diagram, they may choose to follow the blue nodes on the bottom since they have much in common. Twitter networks evolve from people watching how others are connected, and then exploring the unknown person's tweets to see if they are worth following.

After viewing the last map, I have a new connecting strategy for myself on Twitter.

• need more diversity of info/topics/knowledge to monitor
  
• less Digerati, remove several redundant nodes
  
• more Consultants, more interaction with peers and elites in the consulting world
  
• few more local folks, but this cluster is pretty good
  
• look for conversations around electronic music, my hobby
  
• weave a cluster around social network analysis
  
• maybe add a little bit of randomness?
  

The first map is very easy and fun. The second map requires more work... but you get out what you put in!

What does your Twitter social graph tell you?

Update: Perhaps this is interactive Twitter social graph would be pretty useful — if it had your data in it?

Twitter

I used to think Twitter was stupid.

After one week of actual activity, I find it useful.

Twitter is a "micro-blogging" platform that allows you to quickly post short messages[tweets] of < 140 characters. One of my tweets is seen in the graphic above — @dweinberger is the username of another Tweeter. Their power lies not only in their brevity but in their ability to link to other tweets and any other internet content. Twitter's concept is based on the question of everyone answering, in 140 characters or less: "What are you doing?"


I see "What are you doing?" as the wrong question — it focuses too much on daily minutiae, and not on what others may find interesting about you. We still see many tweets of people answering that question faithfully... "I am at the corner of X and Y waiting to meet my friend Z" ... "I am backing up my hard drive"... "reading the morning paper with a perfect cup of coffee". This is info you may want to know from your intimate others, but not from everyone you are reading on Twitter.

I ignore the standard Twitter question and instead use: "What are you paying attention to?" or "What do you find interesting and useful?" Judging from many of the posts I have read, other Tweeters are also using these questions as a guide to post by.

In Twitter you can not read what everyone posts, nor would you want to. You have to select who you want "to follow" — whose posts you want to read. Before choosing who I want to follow, I read a page or two of their tweets and see if they are posting interesting items. Most people leave their posts open to all potential followers, but Twitter does allow you to restrict the reading of your posts to only the people you approve. This is useful for businesses and families and other intact groups that want to limit the conversations to "within the group only". Several consultants also limit their tweets to "clients only" — I do not — see the sidebar of this blog to see my 5 most recent tweets. Some people choose to follow only their friends or acquaintances. I choose to follow who is interesting and who is posting useful information whether I personally know them or not. As we have learned in social network analysis -- it is useful to have "weak ties" to people active in social circles and knowledge pools that are different/complementary to our own.

Twitter is also a great place to ask questions — especially if you have a diverse group following your tweets. Many consultants and analysts find Twitter a great place to get quick answers — anything from how to network Windows and Macintoshes to a citation of an old paper. Journalists often troll the Twitter-verse for story ideas and people to interview.

Twitter is amazing playground for people like me who are interested in social network analysis. Twitter provides all sorts of social network metrics — focus on prestige metrics — on each person's page!

• Following: who you chose to listen to/follow = outdegree
  
• Followers: who chose to listen/follow you = indegree
  
• Favorites: the "chosen few" of who you follow = strong ties
  
• Updated: how often you post a message = network activity
  

Twitter also provides an API for those who want to get access to more data or build an application to work with Twitter. Twitter just purchased a company who had built a nice search engine of the topics being talked about on Twitter, like who is discussing social networks? Or, who is talking about the always interesting Clay Shirky or Duncan Watts? One of Barry Wellman's students was twittering in class — as many students do.

You not need a computer to access the Twitter-verse. Many people send and receive tweets from their mobile phone using their texting service or a mobile web client like Twitteriffic, which works great on my iPod Touch or an iPhone. Mobile devices make it easy to report "news" happening in front of you.

And last, but not least, there is the art of re-tweeting — broadcasting to your Followers what you found interesting/useful from one of the people you follow. By doing this you play the role of Connector by bridging your Followers to another person [Maven] they may not be following. In the networked world, you want to have the reputation as a Connector!

Join me in the Twitter-verse. It is both fun and useful.

Network of Interest

Could you be a "person of interest"?

You might be, and not know it, and not know why.

Last week, the US Congress passed the new FISA legislation. This new law gives the government expanded powers to listen in on anyone they consider a terror suspect, inside or outside the US. While this new law aroused privacy and civil liberties questions, the law's supporters were quick to defend it, and brush off any criticism.

There is nothing to fear in the bill, said Senator Christopher S. Bond, the Missouri Republican who was a lead negotiator, “unless you have Al Qaeda on your speed dial.”

The Senator is very wrong.

You may not have AQ on speed dial, nor be following them in Twitter, nor have their hate sites in your bookmarks, nor have accepted them as a friend/contact on Facebook/LinkedIn, nor be living in the same building as them, but you may still be in their extended social network neighborhood!

See the simple social network map below. Suppose you are the green node at the center, your friends and family are the blue nodes and their friends and family are the grey nodes. This is everyone in your social network within 2 degrees of you. Most people would have dozens of blue nodes and hundreds or thousands of grey nodes in their network neighborhood.


Of all of the people in your extended network, do you know...

• them all?
  
• what they believe?
  
• what they do in their spare time?
  
• what organizations they belong to?
  
• who is in their network neighborhood?
  

You may end up being a "person of interest" if any of the blue or grey nodes in your network have any connection to a terrorist, or to someone suspected of being a terrorist. It is easy to end up in a "bad" network neighborhood — maybe your kid's soccer coach and one of your co-workers each has family back home with the same last name as a well know terrorist? And it could get worse, the watchers could easily expand their field of view and look at everyone within 3 degrees/steps of a suspect. At 3 degrees, we are probably looking at a million node network neighborhood -- easier to be in the same neighborhood as a terrorist then!

By following daily communication, and using current social network analysis methods, the watchers should eventually figure out where the covert clusters of corruption are [if any]. Yet, your life can be negatively affected by the wide net that is being cast. Who wants to be the next Richard Jewell, be falsely accused, have law suits filed against you, and have a "trial by media"?

Release 1.0

This year marks 21 years since I started developing social network analysis software.

The first version I developed ran on a upgraded original Macintosh with an external 20MB hard drive and 512KB [not MB!] of RAM -- I still have the original machine, and dozens of floppies with various versions of the original code. When IBM came calling, "InFlow" [short for information flow] was ported from the Macintosh to Windows 3.1 and OS/2.

In 1996 [some of you were still in high school], I was fortunate to be invited to write about my early social network analysis experiences in Esther Dyson's prestigious high tech newsletter, Release 1.0. Here are my early experiences with social network analysis in large organizations.

Enjoy!

Networks of Voters

Karl Rove and I do not agree on much.

Yet, his op-ed in today's Wall Street Journal does provide an opportunity for overlap.

Rove discusses Obama's 2008 campaign strategy...

"For starters, Barack Obama's manager admitted to the New York Times that he wanted an "army of persuasion" modeled explicitly on the massive Bush neighbor-to-neighbor[emphasis mine] "Victory Committee" of '00 and '04. Those efforts deployed millions of volunteers to register, persuade and get-out-the-vote.

Sen. Obama's organizational emphasis wisely avoids the Democratic mistake of 2000, when Donna Brazille's plea for a stronger grassroots focus was ignored by the Gore high command."

Yes, all politics is local... and social. This is what I discussed in the white paper & book chapter: "It's the Conversations, Stupid!"

"...more than 45,000 canvassers – many hired from temp agencies – to register and turn out voters. It was the wrong model: Undecideds are more likely to be influenced by those in their social network than an anonymous, low-wage campaign worker [emphasis mine]."

Right on, Karl. The strategy of friends talking to friends beats the strategy of strangers talking to strangers — as I described in an earlier blog post from the 2008 presidential primary.

"The Obama campaign is trying to catch up with the GOP's 'microtargeting' program, which uses powerful analytical tools and extensive household consumer information to focus on prospects for conversion and extra turnout help."

And with warrantless wiretapping, the Bush Administration now has very good social network link data on all those "microtargets"! I jest, of course — there have been NO documented cases of counter-terrorism data or methods being used in political campaigns, but... that day is coming.

The bottom line is: the better you know both the nodes and links in the network, the better you can devise a strategy for one local voter to influence another. Help your avid supporters influence their local network.

The map below shows a social network. The grey links show: who talks to whom about politics. The nodes are colored by who they are leaning towards: red = Republicans, blue = Democrats, grey = Undecided. We are ignoring independent candidates in this simple example. How might the Undecideds tip based on the social ties illustrated?

Influencer Targeting

Google has just filed a patent called NETWORK NODE AD TARGETING. Basically, the business method patent is to find the influencers in a social network and place ads on their pages/profiles/sites. In the diagram below, taken from the patent application, we see the steps in the business method.


The field of social network analysis[SNA] has much prior art in the first four boxes [405 thru 420]. Much of the SNA experience is with off-line social networks, though on-line social networks are being mapped and analyzed with increased frequency since the late 1990s. The blogosphere has been a popular source of open source data for social network analysis.

The value-added for Google is to place the electronic ad with the most influential person(s) in the network. Pharmaceutical firms have been doing social network analysis within physician networks since the mid-1960s. Big Pharma has always recruited the most influential doctors to suggest brand new drugs to other doctors in their social circle. And, companies like Visible Path have been selling social network discovery to clients for many years.

So, what makes this Google patent novel and non-obvious???

Independence Day

Happy Independence Day!

So, how independent do you feel?

Most people enjoy the freedom and independence of the Internet. You can go anywhere, read anything, watch anything, listen to anything, almost limitless freedom to do what you please.

On the Internet we make many choices... what to read, what to write/post, what to download, what to watch, what to subscribe to, what to bookmark, what to join, and so on.

We reveal who we are by the choices we make.

An example of these revealed patterns is the previous post on political book purchases.

Yet, as we enjoy the freedom of the net, we are being watched, tracked, mapped and analyzed. We leave a clear set of digital footprints everywhere we go and now we even have GPS and our cell phones to track us off the net. We are not as free nor as independent as we think. It is not just about privacy, but about freedom to choose and the freedom to act.

The precipice we are on, was revealed this past week when a Judge ruled that Google had to hand over, in a legal case, all of the log-in identities and IP addresses [if you have a cable modem you have a static IP address that can be easily tracked to your household] of the computers accessing material on YouTube. Yes, a record of your personal ID and everything you have watched. Wonder what patterns a marketer, psychologist, investigator, or worse -- a hacker, would find in your video choices?

"....for each instance a video is watched, the unique "login ID"
of the user who watched it, the time when the user started to watch
the video, the internet protocol address other devices connected to
the internet use to identify the user's computer ("IP address"), and
the identifier for the video."

We reveal who we are by the choices we make.

Google, is resisting the release of the information -- they would prefer to anonymize the user data before handing it over. Viacom, the other party in the suit, is working with Google and the Judge to minimize any use of your private information. The Judge has stipulated that Viacom can not use the data for marketing, nor harassing you for watching John Stewart on YouTube, instead of their preferred channel. This is a good thing.

We are walking a thin line here. It is just a matter of time before the dots that can not be currently connected, will be connected in the future -- and the key dot is your verified identity. Your autonomy will erode. Your behavior will change. Those being watched act different.

We reveal who we are by the choices we make.

Today's marketing and junk mail is based on obvious connections gathered from public information. Tomorrow's marketing and tracking will be based on private information derived from the choices you make, connected to your various on-line and off-line identities. You will be figuratively naked in front of people you do not even know. Such scrutiny will not just affect privacy, but your autonomy of choice and action.

So, on this Independence Day, how really independent are you?

New Political Patterns

I have been doing a social network analysis of the purchase patterns of political books since 2003. A quick analysis of Amazon's sales data of political books gives us a highly similar analysis to that of political pollsters & pundits. In the past we saw a divided nation in our book buying data. We saw then a distinct red cluster and a distinct blue cluster with very little holding them together in terms of cross-links or books in common.

Now, in June 2008, after the major party candidates have been selected via the long primary season, we again probe the predictive patterns of political polemics. Obama says we are one nation -- not divided into blue and red. McCain proclaims his purple "maverick" roots [purple is mix of blue and red]. What does the book data tell us?

In the network maps, two books are connected if Amazon reports that they were frequently bought together or by the same person. I don't arrange, nor color the nodes before feeding the also-bought data through the InFlow software. The software has an algorithm that arranges the layout of the nodes based on each node's connections, both direct and indirect. Once the software finds the emergent pattern, and any clusters, I review the books in those groups and then see whether they are blue, red or purple.


Once the map was completed, I ran InFlow's network metrics to see which book(s) were most influential in June 2008. Not surprisingly, McClellan's What Happened came out on top, followed closely by Zakaria's The Post-American World.

The purple books [neither Right nor Left] were hard to distinguish this time. According to the network layout algorithm, they are closely integrated with the blues [Left]. Some of the books that ended up purple were surprising. George Will and Patrick Buchanan are outspoken conservatives, I expected them to show up in the red cluster. Maybe this reflects the split we have seen on the Right between the "old conservatives" and the "neo-cons"? The buying data shows that the old conservatives have more overlap with the progressives than they do with the neo-cons! Even Ron Paul's and Jesse Ventura's books link more with the blue than with the red.

Is the country moving from slightly right of center to slightly left of center?

Update: After viewing the network, Micah Sifry @ Personal Democracy Forum, revealed that he sees a simple pattern -- the map shows who is for the Iraq War and who is against. The red authors & readers are for the war, while the blue & purple authors & readers are against the Iraq War.

Welcome!

Welcome to my new blog — T N T.

I have moved many of my posts from the Network Weaving blog to here. They did not fit the focused theme of "network weaving", but do fit under the broader theme of "network thinking" here. I will continue to post on both blogs, but suspect that most posts and new ideas will be shared here first. I see the Network Weaving blog as a place to write about and discuss practical network building solutions. Here there are no boundaries.

All posts before/below this one were formerly published on Network Weaving. All posts above/after this one, will be new to TNT. I will continue to make all posts easily available by scrolling... most recent posts on top.

Please join the conversation via the Comments section and... Enjoy!

It's the networks, stupid

Will Obama's strategic use of grass-roots networks lead to victory in the 2008 U.S. presidential race?

Roger Cohen, who wrote an Op-Ed piece in The NY Times, thinks so. I like the new term he uses: MAC = mutually assured connectivity.

Of course, the Dean campaign thought they understood the internet in 2004, but they really did not get "social networks". They made some breakthroughs in technology, but screwed up the sociology, and lost in a big way. Obama seems to be focusing first on the sociology of building networks and then supporting those social networks with technology -- the correct sequence of attention. The Obama campaign is successful because they know that sociology & technology properly mixed give a better result than either of them alone, or improperly mixed.

Will the social network analysis discussed in this white paper influence the outcome of the 2008 U.S. election?

We'll soon see.

Originally published May 27, 2008

Smoke Rings

Why is this man smoking alone?

Of course, he can't read, but that is not the reason.

Smoking spreads via social circles, and stops via social circles.

Groups that smoke together, also quit together. Those that don't quit with the group, are slowly excluded -- pushed to the periphery of their network -- and end up smoking alone.

Here is the NY Times article on the "social network dynamics of smoking and quitting" published by the same folks that did the social network analysis of obesity. There is also this related article by the Associated Press.

Originally published May 22, 2008

Hub or Spoke?

Often, in social/business situations, we are either a hub[blue node] or a spoke[green node] in the network of interaction and knowledge exchange.

A few months ago, I blogged about how "not to be taken advantage of" if you are a spoke in an interaction. Now my old network buddy, Guy Hagen, tells us how to be an effective hub in a negotiation.

See how these two strategies use similar, yet opposing, network dynamics?

Connect your allies, fragment your opponents.

Originally published May 8, 2008

Pod[cast] of Gold

I will be teaching a graduate level course in Organizational / Social Network Analysis @ Michigan State University during the summer semester. In preparing the reading list for the course I ran across an absolute gem of an article and podcast by one of my favorite network scholars -- Herminia Ibarra.

Herminia is one of those rare academics that can effectively straddle the two worlds of research and business -- she can talk to either audience and translate between the two. In fact, this boundary spanning behavior is an example of her own advice -- bridging between the inside and outside [of whatever organization you belong to] is vital to career success.

Download her interview [MP3] and put it on your iPod and listen to it until you can recite it in your sleep. IMHO, this is the best 10 minute lesson in building effective social networks that I have heard in a very long time!

Listen, learn, and link.

Originally posted May 7, 2008

The DC 5-Step

Last week I posted about how Washington DC lobbyists create an indirect quid-pro-quo to hide how legislation is influenced.

This week we read in the NY Times -- Behind Military Analysts, the Pentagon’s Hidden Hand -- how the Pentagon also uses this 5 step dance to influence public opinion for the Iraq War.


The diagram above shows the strategy described in the NYT article. The goal is to have a positive public opinion for the Department of Defense's [DoD] activities -- in this case, the Iraq War. Public opinion/approval is indicated by the green link. The "message machine" is composed of the grey links.

The grey arrows show the clockwise flow of influence. What is not obvious are the relationships of dependency that move in a counter-clockwise direction. It is these pairwise dependencies that enable the flow of influence. A-->B: A influences B because B is dependent upon A for work/money/information/access.

The NYT article explains how firewalls were set up to hide some of these dependencies.

"The access came with a condition. Participants were instructed not to quote their briefers directly or otherwise describe their contacts with the Pentagon."

Poor traceability enables plausible deniability.

Is it personal opinion or coordinated group-wide spin? Examine the network of social/business ties the "expert" is embedded in!

UPDATE: The Pentagon has put a temporary stop to feeding of information to retired officers acting as military analysts while they investigate the issue.

Originally published April 20, 2008

Indirect Quid-Pro-Quo

We first discovered the Lobbyist's Loop of Deceit when I was mentoring a client doing a network analysis of the recent Lobbying Scandals in Washington. This pattern was most noticeable in the network of Jack Abramoff and his lobbying ecosystem.

Abramoff's clients often wanted to affect legislation in the House or Senate. To avoid an appearance of a direct quid-pro-quo, Abramoff engineered an indirect quid-pro-quo that put great social distance between the client and what they wanted to influence.

The Lobbyist's Loop of Deceit is mapped below. It reveals no direct contact between the client and the target legislation. The greater the social distance between the two, the greater the plausible deniability of both the client and the politician when they are accused of participating in favors/corruption. The lobbyist wants to hide what is happening below the yellow line in the diagram.


A direct quid-pro-quo would have an arrow of benefit/money flow going directly from the Client to the Legislator -- thus creating a tight [and obvious] triangle between the three key nodes in the network...

[Client --> Legislator -->Legislation that benefits Client]

Of course the Client and Legislator do not want to expose their direct ties, so they take a surreptitious route. We know from social network analysis, that the more social distance between two individuals the harder it is to show relation/influence between the two.

Social distance is often measured in the number of steps between two individuals. In this simple network: A-->B-->C, A and B and B and C are 1 step apart, while A and C are two steps apart. Based on social network research on intermediaries and "network horizons" we know that anyone separated by more than 3 steps are usually not known, nor influenced by each other. Plausible deniability increases with perceived distance. In the indirect quid-pro-quo, the client is more than 3 steps from the legislation they seek to influence.

We also saw longer loops that created even more perceived distance between the influencer and the target of influence. In these cases the Spouse node was replaced by a two node relationship where the spouse or other family/friend of the Legislator was a key player in an organization that benefited from the flow of money/influence in the Loop.

Be careful of those who deceive via perceived distance.

Opening Day

Today was Opening Day for most Major League Baseball teams.

It was a great day in Cleveland -- it did not snow, and the Indians won!

During the winter, most baseball talk was about who was mentioned in the "Mitchell Report" on steroid use in baseball. Digging through that report, it is easy to uncover a network -- who supplied whom with drugs. But that network, by itself, does not explain the social dynamics of steroids in baseball over the last decade. We have to look at the social networks amongst players to see:

• how steroid acceptance spread,
  
• how drug sources were shared,
  
• why outsiders were in the dark while it was happening.
  

These dynamics are explained by the dense social networks that develop through the movements of players from team to team via trades and free-agent signings. A dense clique, like the one above [not all networks are pretty]...

• efficiently spreads information -- everyone knows what is going on
  
• maintains conformity -- everyone knows what not to discuss with outsiders
  
• over time, creates acceptance of norms that are aberrant to outsiders
  

For more info, see this short brief on the social life of steroids in baseball.

With many of the "stars" of the Mitchell Report, out of baseball this season, the steroid controversy will be relegated to the court room and not the ball yard.

Play Ball!

Originally published March 31, 2008

Friends talking to Friends

A while back I blogged about the social network strategy of the Huckabee campaign and how it was accomplishing a lot with very little (money). The campaign was using the power of the social tie/link -- friends talking to friends about voting. Good strategy, limited population. Huckabee focused on well-defined clusters, like christian evangelicals, that tend to be very insular and limited in size. With insular cliques, your strategy may work, but it only goes so far -- influence does not cross the chasm to other groups.

The Obama campaign is also following a grass-roots, bottom-up, friends-talking-to-friends strategy as described in the current issue Rolling Stone magazine. To get the vote out, they are using both the Internet AND Obama's experience of F2F organizing. They get the technology. They get the sociology.

In addition, the Obama folks seem to have learned the lesson of the Howard Dean campaign which focused mostly on technology, but were clueless about sociology. Howard Dean's staff organized the Deaniacs over the WWW, but then resorted to the strangers-talking-to-strangers strategy. To accentuate their mistake, they made their activists were bright orange hats which just emphasized them being "not one of us" as they canvassed Iowa neighborhoods. Obama knows that in organizing, locals need to interact with locals.

Yet, the mostly top-down political machine of Hillary Clinton has won elections -- especially the big states. Which strategy will win out? Pennsylvania is the next test. More than a month to go... are the bottom-up networks of influence in place, are locals talking to locals? Or will the top-down barrage of mass media carry the day? Will Hillary borrow the local social networks of her friend and supporter, Pennsylvania's governor Ed Rendell? Are the Obama folks building wide-reaching radial networks, or are they also falling prey to the Huckabee problem of getting trapped in cul de sacs?

Which view will win?

top down...


bottom up...


or both and...

Originally published March 6, 2008

Economic Terrorists: Social Network Justice

One of the pleasures of selling social network analysis software and services is seeing what clients do with the new knowledge and tools we provide to them.

Several years ago I started working with an economic justice organization in a major U.S. city. Their focus is on tenant's rights and eliminating slum housing conditions. They had been working with their city attorney gathering information on a group of slumlords that owned apartment buildings that had a long list of continuously unresolved violations that were affecting the health of the tenants and their children.

They wanted a new way to analyze and visualize their data. Since the slumlords were keeping their activities covert, it made sense to uncloak their network using the data my client had gathered along with other available public data. Instead of mapping jihadi terrorists, the economic justice organization would be mapping economic terrorists.


Originally published February 22, 2008

Duncan vs. The Influentials

Much has been written about how the influential few [an elite 10%] tells the rest of us what to buy, how to vote, etc. There is a book on the topic naturally named The Influentials. A tiny cadre of highly connected elites influencing the rest of us was a key theme in Malcolm Gladwell's The Tipping Point.

Most people would look at the social graph below and say Diane is the influential in this sub-group [all of this group's connections and contacts are not shown]. She has local reach, but her message gets nowhere without the help of her network. Influence needs many connected people to spread -- not just the highly connected. Heather, Fernando or Garth all need to be in a cooperative mood for Diane's message to travel.

In social network analysis, a boundary spanner is someone who "crosses the chasm" between groups/clusters. They are not often highly connected. In the above network Fernando, Garth and Heather are all boundary spanners. They may not be influential, but they need to be ready to accept the message/trend/idea if it is going to make the jump out of their local domain and travel further. Otherwise the innovation/idea bounces around and dies in a cul de sac.

Duncan Watts, at Columbia and Yahoo! Research, has been slowly dismantling "The Influentials" theory. This Fast Company article is a good overview of his argument. He basically says that it is not the elite few that matter but the connected many and they have to be ready to be influenced. I'm with Duncan.

Originally published February 10, 2008

Connected Customers

As mentioned in the previous post, I attended the INSNA Sunbelt conference and had a wonderful experience. The only negative aspect of the event was the conference hotel's awful WiFi service -- and their response to it.

Hotels are used to dealing with disconnected customers -- hotel guests who do not know each other. They can tell these guests anything. Since most guests do not talk to each other, nothing is verified, no action is coordinated. In terms of social network analysis: the hotel staff spans structural holes between the guests -- occupying the power position in the network. Below is a network map of the situation. The centralized hotel staff are shown by the blue node in the middle, while hotel guests are represented by the green nodes. The green nodes only talk to the blue node and not to each other.


When INSNA arrived, the hotel guests were no longer disconnected -- many people in INSNA know each other and after initial greetings started to talk.

The conversation soon went to the lack of connectivity in the hotel -- no one could get a connection out of the hotel to the internet. Not only did everyone discover they were having the same bad experience, but they discovered they were receiving the same lie from the hotel staff -- "everything is fine, no one else is complaining". Being lied to made "being disconnected" all the more infuriating.

Soon "emergent clusters" of INSNA members went to the front desk as small groups and started demanding better service -- after all we were being charged for WiFi. The front desk manager became overwhelmed by the coordinated action and soon went into hiding and refused to talk about the topic. A network illustration of the connected INSNA hotel guests looks different. Because the green nodes are talking to each other and coordinating a strategy, the big blue node is now more constrained in it's response, and ability to act.


Eventually, wifi service improved, but not to the level one would expect in a business class hotel.

This white paper shows how power dissipates when people in a hub-and-spoke network [a.k.a. hierarchy] start to talk to each other.

Power dissipates, and learning begins.

Originally published February 6, 2008

Network of Social Network Scholars

Last week June and I attended the Sunbelt Social Network conference, sponsored by INSNA -- the network of social network analysts.

It was great conference focusing on all aspects of social network analysis. When it started in the 1970s it was an academic conference, but every year, as of late, more and more practitioners show up. Both June and I did presentations of our recent work in community network mapping and weaving. Great people [old friends, new friends], great weather, well organized, great conversations! Thanks to John Skvoretz, Chris McCarty, Russ Bernard and all of the other organizers!

The organizers provided a goodie bag and inside was a nice USB jump drive with some social network data on it! The author and co-author data was gathered by Chris McCarty from the field's top journal: Social Networks. I took the coauthor data and made a little web app from it. It is a simple network mashup that connects the coauthor network to Google Scholar.

Enjoy!


Originally published February 2, 2008

Social Networks: 1 Political Machine: 0

The first U.S. presidential primary of 2008 is over and it was full of surprises. After the first inning, we have an unexpected lead.

One of the biggest shocks was on the Republican side -- Huckabee beat Romney. The low budget guy beat the the big spender -- shocking all of the pundits. The common wisdom in politics is that money wins -- s/he with the biggest machine marches on. Since Huckabee couldn't outspend his rivals he had to out-think them. [Lack of money frequently leads to creativity]. Huckabee chose to network his way to success. From USA Today:

"Huckabee, whose campaign has caught fire only in recent months, is largely relying on pre-existing networks within Iowa, ..."

He found local social networks of conservative Christians, gun owners, home schoolers and tax reformers. It was in these networks that Huckabee's message caught fire and spread to other networks that intersected with these. Soon Huckabee had large clusters of interconnected supporters, all reinforcing one another -- friends talking to friends.


Meanwhile, Romney and the others where following common campaign wisdom and setting up phone banks, canvasing neighborhoods and spending money in the mass media -- strangers talking to strangers.


What was the big difference between these two approaches? Huckabee was connecting to intact networks that had a long history together, while Romney was connecting to individual voters -- one at a time. While Romney's supporters were also members of social networks, they were talked to, and influenced individually, alone. Who knows what they did when they went back into their social network? Huckabee's networks all got the same message at roughly the same time -- they probably had very fewer defections.

From Jonathan Tilove @ Newhouse News:

...ultimately, for all the talk about voting being a private act, it is in fact a social act in which individual behavior is hugely dependent on the thinking and actions of others.

Messages to people alone on the phone, alone in the car[radio], alone on the couch[TV], alone with the newspaper, alone with the computer, don't STICK the same way messages conveyed in a group of trusted others. Alone, we hear the message, forget the message, make the promise, forget the promise. In a group, we hear the message, discuss the message, internalize the message, make the promise to the group, keep the promise to the group. Huckabee supporters were more likely to remain in support for their candidate during the caucus process, than Romeny's supporters -- who promised support when alone, but had to act in a group at the caucus.

As I was thinking about these social network dynamics of voting, I got an email from Debra -- who had been entertaining similar thoughts...

"... and immediately thought of your "Conversation Stupid" article after Huckabee's upset win in Iowa. I told an economist / blogger friend a while back not to underestimate the power of Hucklebee's social network -- especially from the home-schoolers. I am a Democrat (former Republican) in a very red district in southwestern Ohio. I recently forwarded your article to some of my colleagues in our county party, along with my cliff notes. Unfortunately, the Democratic Party puts a lot of emphasis on phone-banking and door-to-door canvassing, but I am convinced that "brute force" methods such as these are ineffective. Our party is small and insulated in southwestern Ohio and I'm afraid it will stay that way if we rely too much on cold-calls to strangers."

In 2004, George W Bush won Ohio and therefore the presidency -- Ohio put him over the top in the electoral college. In several conversations I have had about the 2004 Ohio election I have been told that Bush won his slim majority in Ohio by also connecting to existing social networks. The Bush campaign used the social networks connected to churches throughout the state -- not just evangelicals, but Catholics and Protestants also. The extended social networks of a couple hundred churches roughly equal Bush's 119,000 vote margin in Ohio in 2004.

We have heard that "all politics are local", now we also find out that "all politics are social".

Updates...
Huckabee continues "networking strategy" in Michigan
{Hat tip to Jill}.
Huckabee's social network army
{Hat tip to David}.

Originally published January 4, 2008

Looking Forward to 2008

Change will be happening in 2008, both technologically and socially.

One of the most important events of the new year in the U.S. will be the presidential election. The first primaries happen just 3 days into the new year -- January 3rd in Iowa. What affect will these early choices have on the overall electorate?

A very interesting article on the social network dynamics of elections by Shankar Vedantam was published in the Washington Post today. Shankar quotes the recent research of Duncan Watts that reveals it is often the local patterns in networks that influence how people think about events and people. And, these patterns can act differently depending on the information they are fed. Watts also points out the high influence of those people who act early in the process -- the voters of Iowa and New Hampshire.

I wrote a chapter for the book Extreme Democracy a few years ago that also looked at the social network dynamics of voting behavior. Based on the literature review, I reached a similar conclusion to that of Watts -- "it's the [local] conversations, stupid". People are influenced by what those around them think and do -- including choosing to vote, and who to vote for.

It is also time to do another political book network map -- the last major version was done for the 2004 U.S. presidential election. I created a interactive political book network for the 2008 election. It is an interactive map that you can play with, move books around, hide them, etc., and see what emerges! Just click the Help button, in the above link, for instructions on how to interact with the map. Enjoy!

Watch how your local social networks react to the election -- share your observations in the comments below.

Happy New Year!

Update: Great new article by Jonathan Tilove on complexity and networks in voting featuring Duncan Watts.

Originally published December 31, 2007

Military Intelligence

Military Intelligence — No oxymoron this time.

The graphic above [from Gizmodo] points to a smart move by the US Army. The army is diversifying their computer networks with both Macs and PCs to make the networks robust and resilient under attack. They started using Macs in the late 1990s to confuse hackers who only knew Windows hacks[which is still the majority of black-hat hackers].

Smart farmers have always planted diverse seed sets... if one strain of corn/soybeans/etc. is attacked by disease, the others usually survive. The goal is not to avoid attacks -- they will happen -- but to have your complex systems degrade gracefully, instead of collapse suddenly. When your systems can sustain attacks, without sudden failure, you have time to recognize and fix the disruption before it causes much damage.

Social networks need diversity also -- not just the typical gender/race/orientation types of diversity. But knowledge diversity coming from various knowledge pools, ways of learning, backgrounds, and ways of seeing patterns & solving problems.

Innovation happens at the intersections -- where diverse knowledge meets and mixes.

Happy Holidays to All !

P.S. Mix some knowledge while you mix those holiday drinks, eh?

Originally published December 22, 2007

Location, Location, Location

The golden rule of real estate [location, location, location] is also golden rule of social networks. In real estate, its your physical location -- your geography. In social networks its your virtual location -- your "socialography". One is visible, the other mostly invisible. Yet, they can both be mapped and measured.

Here is an excellent NYT article about how geography and socialography intersect in Silicon Valley.

“... in Silicon Valley, you locate a company where the engineers are”

"These microclusters turn out to be a very efficient way to innovate, to see what works and what fails, and do it extremely rapidly"

This article explains why people are willing to pay $900,000 for a home in Silicon Valley that they could have for $150,000 in Cleveland [or Orlando for sun worshippers].

This NYT article is along the same theme as our previous posts on Knowledge Spillovers and A Perplexing Economy.

Originally published December 20, 2007

Those close by, form a Tie

Birds of a feather flock together... so do entrepreneurs.

Ed Morrison found some interesting research that examines the dense clustering of successful economic neighborhoods/clusters. This research is similar to that of Thomas Allen @ MIT, who studied how engineers and scientists worked, and from that came the Allen Curve, which shows the correlation between distance and frequency of communication in organizations. Both sets of research support what I have observed in social network analysis projects: those close by, form a tie -- and as a result get things done. In the age of the Internet, physical distance still matters!

From Washington University in St. Louis, News & Information:

"High-tech firms locating close to each other benefit from the proximity," says Barak S. Aharonson, visiting assistant professor of organization and strategy at the Olin Business School at Washington University in St. Louis. "The potential for frequent face-to-face interaction, serendipitous encounters and easy scrutiny are facilitated by being near firms that are working on similar things and are open to sharing information."

Coffee shop encounters could lead to new business ideas. These "knowledge spillovers" happen more frequently the closer firms are to each other, and dissipate as the distance between companies grows. In fact, Aharonson said, the benefits of agglomeration are strongest within 500 meters (about 0.31 miles) and fade quickly over distances.

"Eventually they are all going to meet in the nearby coffee shop. The basis of agglomerations and the benefit for high tech firms is the flow of knowledge," Aharonson said. "At this point high tech knowledge is almost a public commodity. You can protect it, however through interactions with people — especially those outside the company — it disseminates rapidly. Proximity facilitates face to face interaction and increases the likelihood for knowledge spillovers. These knowledge spillovers enhance the potential creativity of the scientists. Increased creativity leads to new ideas, new products and new businesses. Hence, closely located firms are more likely to benefit from such knowledge spillovers than isolated firms."

Here is the full paper on Knowledge Spillovers.

Via BrewedFreshDaily.

Originally published December 16, 2007

Investing in Social Network Analysis

CNET is reporting that social network analysis company, Visible Path [VP], is about be acquired by a very large firm.

I am glad to see this success. VP is one of the few businesses focused on social networks that actually know what they are doing -- no smoke and mirrors, nor beacons here. Just good science and good business. VP has some of the elite academics in the field of social network analysis as executives and advisors. Congratulations to Stanley Wasserman and his smart network!

UPDATE: Stanley Wasserman has confirmed the deal to me, but he can not disclose any more at this point in time [12/05/2007].

Originally published December 4, 2007

A Perplexing Economy

Recently a study of the Cleveland economy was commissioned, by a local real estate developer. It got the attention of local blogger John Ettore, who was then noticed by NEO super-blogger, George Nemeth. The study is summarized nicely:

"Cleveland is a perplexing economy," according to Dr. Christine Chmura, President and Chief Economist of Richmond-based Chmura Economics & Analytics, "It should be growing faster than it is because the industry mix is more favorable than the state and the region has so many attractive qualities such as the arts, cultural attractions, recreational opportunities, and professional sports teams."

The key word here is "should" -- emphasis mine.

So, the nodes seem to be in place -- industry mix, cultural attractions, etc. But the economic network/ecosystem is underperforming. Why? Maybe, it is lacking links -- the interconnections between clusters of knowledge and ability that make things happen and get things done in today's economy. Innovation happens at the intersections. Innovation creates new businesses and jobs. Innovation attracts other innovators -- people who know the dance, and want to be with others that know the dance.

Silicon Valley[SV] is known to be a place of innovation. A recent example illustrates the power of intersections. Apple did not create the iPod by itself. It did so with several SV neighbors who had the tech/knowledge that Apple did not have -- innovation happens at the intersections. Apple then took the design created in California, by the intersected firms, to its international network and got it built and distributed.

We all know "It's the economy, stupid!" And in today's economy: "It's the connections, stupid!"

Is it possible that the Cleveland economy looks like this -- many players, many islands, few intersections...


Whereas, the Silicon Valley economy might look like this -- many players, no islands, many intersections...


Originally published December 2, 2007

Email = Social Graph?

Forget about Facebook and MySpace for your social graph.

A recent BITS column in NY Times mentions making your email history a lens on to your social network/graph. Both Yahoo and GMail have plenty of data. Microsoft does not have the data, but a big opportunity when you consider all of the email history residing on corporate Exchange servers.

Above is an email social graph, gathered from an Exchange server of a client. Purpose of the social graph was to provide a visual map to project leadership to help get their project unstuck. Social network analysis was applied to spot key connectors, clusters, bottlenecks, and measure the flow of information between the various groups in the project.

Originally published November 25, 2007

Social Graph

This week we witnessed a tipping point for the term "Social Graph" -- originally a term used by mathematicians and sociologists -- currently the buzz of the social web community. When the designer of the web, Tim Berners-Lee [TBL], wrote a rambling post on the "Social Graph" the tipping concluded in a load cacophony of bloggers commenting on the concept.

One of TBL's insights was very simple, yet useful. He explained how Internet is changing focus from the connections between computers to the connections between people. Sir Tim explained the change using three, three-letter acronyms. First, he started with the III - International Information Infrastructure, in the USA it was originally known as the National Information Infrastructure. It grew up to be the Internet. On top of the III, TBL built the World Wide Web. And finally he sees the GGG, the Giant Global Graph, which will be built upon the existing technology of the III and WWW.

• III - how computers are connected
• WWW - how documents are connected
• GGG - how people are connected

It is now obvious -- computer scientists and mathematical sociologists are long lost cousins!


The diagram above is my social graph from a very early on-line social network [OSN] -- Ryze. I am the green node in the middle, my friends in the OSN are the blue nodes, and their friends [my FOAFs] are the grey nodes. The red links show my connections and the connections amongst my friends and grey links complete my 2 step paths to the many FOAFs. As time went on, and more people joined the OSN, my social graph grew, but it never approached my actual social network -- it was only a slice. A slice of my real life.

Yet, slices are useful -- they show us a particular place at a particular time in a particular state. This is how CAT [computer assisted tomography] scans work -- their photographic slices of our complex bodies help doctors diagnose our ailments. You need the focused slice to understand, looking at the whole often results in overwhelming confusion.

Do we need the whole GGG? Yes, like a map of the world, and GPS, it will have applications. Yet, most of us are much happier with local maps [local to our network -- within a few links of us], revealing local dynamics for our local lives. If a freeway stops in Los Angeles, does the Cleveland commuter care?

Originally published November 23, 2007

Only Connect

"Only Connect" -- sounds like a quote from Web 2.0 marketing materials, or from a social network analysis guru, or from a network weaving coach. Definitely a quote from the 21st century... right?

Nope.

That quote is almost 100 years old, and it is from E. M. Forster, the author of a prophetic short story -- "The Machine Stops" -- written in 1909. The short story foretells the internet in a most amazing way. The Machine is the pervasive communication device/network between all living spaces/apartments beneath the surface of the planet. People live below the surface because of an environmental disaster above ground.

Two main characters in the story -- a mom and a son. The son longs for F2F contact, while the mom enjoys The Machine and makes a living doing lectures, which are delivered like podcasts and conference calls. She has a "crackberry withdrawal" in one passage where she panics because she is away from The Machine and her messages are mounting. The "call center" for The Machine is a laugh. The fear of The Machine is not.

Tonight WCPN 90.3 FM in Cleveland broadcast an adaption of the story for radio. WCPN will re-broadcast the excellent show Monday, November 19th @ Noon eastern time. You can listen live to WCPN.

Interviews with the creators of the radio play are also available.

Enjoy!

Originally published November 16, 2007

Networks, Patterns & Paintings

I have shared the story of a client saying one of my network maps reminded him of a Jackson Pollock painting. That is J.P. above starting a new painting. [ I never do my network maps standing on one leg.]

Various mathematicians and physicists have looked for mathematical patterns, like fractals, to discover fundamental building blocks present in biological, social, and man-made networks. Now, some of these same number-crunchers are applying their algorithms to a group of recently found paintings -- suspected to be by Jackson Pollock. Are these real? Or are they fakes? Maybe mathematics and motifs will tell us. An initial study of these paintings cast doubt on their authenticity. Now, a group of physicists from Cleveland's Case Western Reserve University have come out with what they say is a better analysis.

We as humans leave behind repeated patterns and motifs in our architecture, music, writing, and social networks... so why not in how we paint?

Originally published November 11, 2007

What's the "Network"?

Above is a typical social network map [social graph]. It shows the connections amongst various members of an on-line social network [OSN]. Based on data gathering methods, originally developed by academics in the field of social network analysis, this is what most social network maps look like -- a focus on the largest connected component.

Yet, is that everything? Is that the whole community or just the obvious part? Maybe there is more? Are people attracted to the core community, but not yet connected to it? Are people interested in the network, but still lurking around the edges -- waiting for an intro/invite or opportunity to step forward?

Maybe our social networks, er... spaces, look more like the image below? Notice that the map above[red nodes] is only a small portion of the map below[red/green/blue nodes].


This social graph is taken from an actual on-line community that reveals active, semi active, passive and dormant members. Think about social networks and communities you belong to... Is everyone connected to everyone else [by some path]? Or, are their part-time members? Observers from the outside? Sympathizers? Spies? Passive supporters? Orbiting clusters?

IMHO, all of our networks are like the later picture, with very fuzzy borders and overlap with other social spaces. Maybe this question: "Is Z in X's network or Y's network?" does not make sense. Maybe the answer is "Yes!" We are all in multiple networks in multiple ways with multiple strengths of membership. Welcome to the Social Space... you have been here all along! Like fish may not be aware of water, we may not be aware of the fuzzy/overlapping/interacting social circles/clouds/clusters we are all embedded in and floating around in.

Enjoy the self-organizing serendipity of who you will bump into next!

UPDATE: Maybe the name of this post should have been "What's the Graph?" The hot term in 2007 is "Social Graph".

Originally published November 1, 2007

Social networking... in your garden

It appears that social networking is a hot trend all over this planet -- above and beneath the surface of the earth. Social networks are not limited to livings things with individual brains.

It has long been known that Aspen trees survive and thrive via internetworked root systems. Interesting research from Holland now reveals that many small garden plants are not "individual" plants, but interconnected networks. They send each other messages about the local environment, like warning of a "caterpillar attack".

Each plant monitors the periphery of its network to adapt... pretty smart, eh?

Originally published October 5, 2007

"A Space" for Mr. No Face

It looks like the U.S. intelligence community [IC] will be social networking soon. Following the old Rand Corp. adage -- It takes a network to fight a network -- the IC will try to bridge the silos that have been their Achilles heel for decades.

They will build a My Space/Facebook clone called A Space -- "A" stands for agent/analyst. Rather than social networking, their true aim will be closer to knowledge networking -- sharing knowledge and insights from all of the data they have gathered.


Will innovation happen at the intersections? Or, will the strong IC culture of "Need to Know" remain as "Need to NO!" -- as in: NO sharing of information/insights outside of our tight little group. Will this be another example of great technology married to lousy sociology? Hoping that new technology will overcome the human tendency to repeat what is familiar and safe?

IMHO, just putting social web technology into a strong culture, averse to sharing and connecting, will not change how things get done. My Space and and Facebook worked because they were dropped into cultures eager to connect. The IC needs to get the sociology right before they pick a new technology -- or the two need to emerge and adapt together.

Originally published August 24, 2007

Leading Indicators

Once we map a network, we can also measure it.

But how do you measure a network? Academics have come up with hundreds, if not thousands, of various metrics which arise mostly out of the fields of graph theory, network science, and mathematical sociology. Here are some of the common metrics used in social network analysis.

Network weavers and community builders want practical metrics – that are globally understood, without an advanced degree. Several of our not-for-profit clients are being evaluated by the Foundations that fund them on their network/community building activities. Here are four simple metrics that are currently being used...

• Increase in Size of Network -- attracting new people to the mission
  
• Increase in internal network connectivity -- connecting the right people to get things done
  
• Increase in connections to valuable third parties -- bringing in outside skills and perspectives
  
• Increase in projects formed with all of the above -- creating value-added projects out of the interconnected skills. The diagram above shows thick lines which indicate new collaborations formed in the last 3 months.
  

We have found that increases in the above 4 metrics are leading indicators of good things to come for members of the network. Once many of the right connections are in place, and in use, prosperity usually follows.

How will you knit your net?

Originally published August 2, 2007

Birds of a feather, grow fat together

The graphic above, from a social network analysis, shows how a contagion spreads in a human community. A contagion can be an idea or a disease. Communicable diseases such as TB, SARS, H5N3 [bird flu], HIV/AIDS, all spread with the help of social/contact networks.

Now researchers have found that Obesity also spreads via a network. If you friends are fat, the data says, soon you may be fat also!

"What spreads is an idea. As people around you gain weight, your attitudes about what constitutes an acceptable body size changes, and you might follow suit and emulate that body size," Christakis said. "It may cross some kind of threshold, and you can see an epidemic take off. Once it starts, it's hard to stop it. It can spread like wildfire."

"People are more likely to copy the actions of people they resemble," Christakis said. "What we think is going on here is emulation."

The amazing pattern was that friends are more influential than spouses or siblings in determining your weight. This confirms why groups like Weight Watchers are so effective, while our worried spouses may not be. Alcoholics Anonymous also follows this peer influence model to keep its members from over-drinking.

Original The New England Journal of Medicine paper by Nicholas A. Christakis and James H. Fowler.

Originally published July 25, 2007

The world may be flat, but it is bumpy also!

Every week we hear about globalization and the loss of U.S. jobs to foreign countries where labor is cheaper. But labor is not the only cost of doing business. Good supply and distribution networks are critical. In a "flat world", connected by information technology, the supply networks are in place and the work flows to the cheapest locations -- Mexico, India, Pakistan, China, and others.

But, if labor is cheap, and the network is unreliable, the "flat world" equation no longer computes! All of the above mentioned countries have recently experienced large worker protests, infrastructure attacks, or both. Mexico and Pakistan seem to be at the greatest risk.

A recent report by Reuters...

MEXICO CITY (Reuters) - Up to 1,200 companies in Mexico have stopped production because of problems with the supply of natural gas following a rash of pipeline explosions caused by rebels, an industrial group said on Thursday.

The leftist Popular Revolutionary Army, or EPR, has claimed responsibility for four attacks to state monopoly Pemex's pipelines carrying natural gas, liquefied petroleum gas, crude oil and gasoline over the past week.

"There are more than a thousand, nearly 1,200 companies, that have been greatly hurt because of the lack of (gas) supply," industrial group Canacintra's head Victor Manuel Lopez told Reuters.

Automakers like Honda Motor, Nissan Motor Co. and General Motors are among the companies hurt by the blasts, he said.

How long will Honda, Nissan, GM and Ford put up with unreliable supply networks in Mexico? Not long. Their just-in-time manufacturing processes will just hasten their alarm and planning. When you compare unreliable supplies and increased security costs to UAW wages all of a sudden that unionized Michigan and Ohio auto plant makes more $en$e.

If the auto plants move back north, more jobs will become available in US auto industry. But all will not be well -- the US-Mexico border will feel more pressure as more Mexican workers want to cross. A complex interconnected system is always full of such good news/bad news scenarios -- a pull here results in a push there.

For more on how "global guerrillas" are disrupting globalization follow John Robb's excellent blog or read his book, Brave New War.

UPDATES:
1) On 9/11, another bomb blast in Mexico and another car plant is idled. A "flat world" with craters. What's the true cost of manufacturing in Mexico?
2) The pattern continues...

Originally published July 23, 2007

Innovation Happens at the Intersections

Innovation happens at the intersection... of two or more different, yet similar, groups.

Where...

• one technology meets another
  
• one discipline meets another
  
• one department meets another
  
• one network meets another
  
• one neighborhood meets another
  
• the forest meets the meadow
  
• the ocean meets the shore.
  

The intersection of Art and Technology will be highlighted at Cleveland's Ingenuity Festival next week. Art, dance, music, theater and technology remixed through a long weekend: July 19th - 22nd.

I was first introduced to the intersection of art and technology many years ago when a client told me, after a long examination of a social network map of his organization, that my network diagrams reminded him of Jackson Pollock paintings! I took that as a compliment, and the art/tech seed was planted for me. Hmmm... I thought... analytic data visualizations as art... could be!

As a prelude to the Ingenuity Festival, Cleveland State University is holding a public forum on Creativity and Technology. Come hear more about Innovation at the Intersections!

UPDATE: For a more detailed examination of Innovation at the Intersections come hear Ed Morrison and Valdis Krebs at the Synergy Speaker's Forum, Saturday, July 21st @ Noon during the Ingenuity Festival.


Originally published July 10, 2007

We are watching...

Siva Vaidhyanathan led off the New Network Theory conference with the first presentation on Thursday morning.

Later we sat down for lunch and before he could bite into his sandwich, his Blackberry buzzed... he got a Google alert... about himself... speaking at the New Network Theory conference. Less than 1 hour had passed since he finished his talk.

The whole world is watching... in real time.

Who are you tracking with Google Alerts?

P.S. Siva's Blackberry should be buzzing in a few minutes.

Originally published July 8, 2007

1 Day F2F = 1,000 emails

We often get the technology right, but forget about the sociology and then wonder why our computing systems do not live up to expectations.

Here is an excellent article on why the social is so important in social computing. We tend to focus on the computing, because that is easier. The article discusses where email and other on-line collaboration works well and where it does not. It also discusses how the lack of non-verbal cues [oral and body language] can quickly lead to rage in on-line discussions.

Email is great for sharing data, simple facts, and process updates, but not for "making sense" of complex problems. For that you need a richer media -- like real-time, face-to-face. Just like a picture is worth a thousand words, a day working face-to-face is worth a thousand emails... and probably more!

OK... 1 Day F2F > 1,000 emails

Originally published July 4, 2007

OSNA - Open Source Network Analysis

Occasionally we are unaware of what is obvious to everyone else.

Talking with a client this morning, revealed a BGO [blinding glimpse of the obvious] for me. "You specialize in OSNA -- open source network analysis", he said. "Look at all of these networks you have mapped with data from the Internet", he continued.

• Internet Industry Partnerships
  
• Political Book Patterns
  
• 9-11 Hijackers
  
• Mideast Conflict
  
• Academic Co-authorships
  
• Economic Development Community in NE Ohio
  

With SNA tools getting easier to use and more available to non-experts we will see more "open source intelligence". The Christian Science Monitor spotted this trend in their 2007 article: The Wikipedia way to better intelligence

Advanced technology and Web-savvy citizenry now make it possible for open-source information gathering to rival, if not surpass, the clandestine intelligence produced by government agencies.

Indeed, open-source methods have already proved their worth in counterterrorism. Shortly after Sept. 11, Valdis Krebs, a security expert, re-created the structure and identities of the core Al Qaeda network using publicly available information accessed from the Internet. He started with two 9/11 hijackers, Nawaf al-Hazmi and Khalid Almihdhar, who were identified from a photograph taken while they attended a meeting with known terrorists in Malaysia in 2000. By scanning public sources for information linking these suspects to others, he re-created the social network identifying all 19 hijackers and described their relationships to their coconspirators, including the identification of Mohammed Atta as the ringleader.

I will discuss OSNA at the New Network Theory Conference in Amsterdam, 28-30 June, 2007. Of course, Richard Rogers [organizer of the above conference] is the true master of OSNA! Look at some of the maps from his Issue Crawler.

First, we had SNA [social network analysis], then Gerry Falkowski came up with ONA [organizational network analysis] -- to sell SNA to corporate executives -- and now we have OSNA.

Next?

Originally published June 13, 2007

Bright Future for Social Network Analysis?

Good advice from the Gartner Group at their Symposium/ITxpo: Emerging Trends this week.

They gave 4 core messages for Leading Edge IT Change. Message #1 includes social network analysis.

Gartner said that Social Network Interaction is where leading-edge
companies will make their mark and wield their influence. It advised
CIOs and IT leaders to:

* Expose your trickiest business and technology challenges to open forums and learn how to identify real contributors.
* Solicit and respond to customers' input, feedback and new service ideas through communities of customers.
* Use social network analysis software to map out how information and ideas flow among your people across regions, continents and business entities.

Glad to have Gartner aboard the bandwagon!

Operators are standing by...

Originally published May 25, 2007

Philanthropy Networks

David Lazer points to an interesting article in the Boston Globe on how our personal networks influence our political behavior and our donating behavior to particular candidates. This quote from the article sums it up well:

"You don't give to causes, you give to friends".

So, how do you use this lesson to motivate the non-givers in the social network map shown above?

Originally published May 7, 2007

Companion Planting

Attended the Defrag conference at Lorain County Community College [LCCC] these past two days. What a wonderful facility LCCC has!

Just like the last Defrag, I had an ah-ha moment at this one. This moment came from one of the other attendees -- Soren H. We were discussing connections in regional economies after my presentation. He said, "I think what we need is something akin to 'companion planting', after all isn't an economy a lot like an ecosystem?" Economy = Ecosystem? Sure! "But what is companion planting?" I inquired. He explained that it is a concept from organic gardening -- plants can benefit from having certain other plants close by in the garden. You can create the right mix to benefit the whole garden.

Of course! An economy that has the right mix of connected talent will work in the same way. Each benefits from having the other nearby resulting in creative combinations and win-win scenarios while the garden/economy benefits the most from the combinations and connections.

Which combinations and connections are best for your regional economy?

Originally published April 13, 2007

20 Years of SNA/ONA

This autumn[2007] I will celebrate 20 years of doing "practical social network analysis" in organizations and communities. Some things have changed, others have not. Software and hardware have seen vast improvements in capacity and speed. Yet, the most popular social network metrics remain Freeman's centrality metrics -- Degrees, Closeness and Betweenness.

I recently gave a presentation on those 20 years in Galway, Ireland at the Digital Enterprise Research Institute [DERI]. I could not discuss all the 500 or so SNA and ONA projects I have participated in, so I chose a "Top 40" -- ones that were both interesting, and I had permission to publicly discuss. An abridged version of the presentation is available for viewing.

Twenty more years and I think I'll call it a career -- I never regret the day I chose to leave the corporate world and become an entrepreneur.

Originally published March 11, 2007

Holiday Networks

David Lazar has a great holiday post on his blog -- all about how holiday family get-togethers help weave, and strengthen, the family network. These reunions help maintain the connections between the many spokes in the network [usually the siblings and cousins].

After the festivities are over, here is something to ponder while sipping the last Eggnog... Above is a picture of winter in Latvia [for you urbanites, and Equator-huggers, this is what a sleigh ride to Grandma's house may look like]. What does that picture reveal about our networks? Please answer via the comments.

Happy Holidays, and an Innovative New Year to All!

Originally published December 24, 2006

Listening to Networks

Previously, I had blogged about putting social networks to music.

Today, Studio 360 [heard on WCPN 90.3 FM in Cleveland] did a fascinating radio piece on Brain Music [MP3]. The brain music sounds a lot like famous minimalist composers such as Riley, Reich, Pärt, Glass, Cage, and Adams.

More details and sonifications of brain music are available on this University of Minnesota Brain Sciences Center page.

The brain is made up of many overlapping networks resulting in massive connectivity. So, is brain music really network music? Will clients soon be asking for musical scores instead of centrality scores?

Originally published December 17, 2006

Famous Predictions, Gone Wrong...

1899

Everything that can be invented has been invented

1943

I think there is a world market for maybe five computers

1977

There is no reason why anyone would want a computer in the home

1981

640K should be enough for anybody

The 2006 YFM! Prediction Award goes to...

"Analysts at the research and consulting firm Gartner Group believe that by next summer there will be 100 million people with blogs, and that will be it. Discussing the firm's annual package of "Predicts," Daryl Plummer, the managing vice president, said growth will plateau because after five years or so, anybody who wanted a blog already has one."

quoted from Frank Barnako's Internet Daily

Originally published December 15, 2006

Election Day

Did you vote today? Chances are your decision to vote, or not, was influenced by your social network. Both, if we vote, and who we vote for, is influenced by conversations we have. I wrote a book chapter for Extreme Democracy on this topic.

Here are links to two of the top researchers in the field of "social networks and voting behavior" Robert Huckfeldt, James H. Fowler.

See their web pages plus the bibliography of my chapter for some fascinating reading of how networks affect the vote.

P.S. Tell all of your friends who have not voted yet, that you voted today... especially those friends who lean towards your views! ;-)

Originally published November 7, 2006

Making Introductions

patternHunter observes...

One of the challenges with "social networking" sites is that most are more correctly "social linking" sites.

...they are all like bad parties where everyone is gathered in small circles with their backs to anyone new. One of the benefits of a good host/hostess (other than attracting an interesting crowd) is his/her ability to introduce individuals to other individuals who are likely to share some kind of interest. To my knowledge, no social networking site is particularly good at making introductions and most do not even try.

Yup. The best introductions are made around a goal -- we connect better when we work together.

Bloggers and Innovators

In early 2005 we took at look at two networks in NE Ohio...
1) Bloggers and 2) Innovators.

Our initial goal was to map these communities -- to see who was in them, and who played the role of Connector and Maven. Connectors and Mavens come from Malcolm Gladwell's book, The Tipping Point. Connectors link different parts of the network that would otherwise not be connected, while Mavens are key resources that others go to for advice, opinion and expertise.

In looking at these two networks in NEO, we see some overlaps. Some of the same people pop up in both the Blogger Network and in the Innovator Network. We also see overlaps between Mavens and Connectors -- some people play both roles. Are these key influencers in reforming our regional economy?

In the graphic above we see both the map of the Innovators and their collaborators [zoomed-in to a particular section], and the metrics to find the Connectors on the map -- listed high to low.

Originally published October 17, 2006

Connecting after Katrina

Many people think that all post-Katrina recovery efforts are fragmented and failing. Although many of the formal organizations are falling over each other, and over the debris that is still in the streets, community networks are self-organizing and emerging in New Orleans and elsewhere in the devastated region.

A month ago, I got an email from Sarah who is working with ThinkNOLA. She inquired...

Through the New Orleans Wiki we've documented significant social relationships and organizational connections between board members in the key recovery agencies, both governmental and quasi-governmental. Do you have any suggestions for producing visual representations of this information?

I said, "Sure, put your data into this link/relationship format, send it to me, and I will map it for you." BTW, this is a great use of WIKI technology -- a common place for people to store/edit/update the relationships/flows they find.

We went through several iterations of data and soon had some maps. The network above is a combination of all 8 relationships we mapped. It shows how over 1000 organizations and individuals are connected in various recovery projects.

The NOLA network has grown to the 'multiple hubs' stage that we described in this white paper: Building Smart Communities through Network Weaving [PDF]. ThinkNOLA and their colleagues are examining the first set of maps to see where they are -- who is connected, who is not and who should be. They will then weave the network where necessary.

An iterative process: know the net, knit the net... repeat.

Originally published September 17, 2006

Brains vs. Bits

I often discover new knowledge by looking at who links/refers to my web site.

This morning I was reviewing who visited my web site and saw a link from a Scottish government web page. Reading other content on that page, I discovered this interesting study:

Research reveals how knowledge is accessed within organizations:
• Employees brains 42 per cent
• Paper documents 26 per cent
• Electronic documents 20 per cent
• Electronic knowledge bases 12 per cent

(Source: The Delphi Group)

The complex knowledge held in people's brains is what gives an organization its competitive advantage. It is context sensitive and cannot be codified, written down and stored.

Not a good study for those who believe I/T solves everything. Too bad the year of the study was not given. But, given the source of the study, I would guess it is not before the internet became popular.

Originally posted on August 25, 2006

Team Networks --> Team Chemistry

Teams are not made of talent alone.

It is how the talents of individual players intersect and interact that distinguishes a good team from a collection of good players. From the New England Patriots, to the Detroit Pistons, to the Chicago White Sox -- teams without a superstar at every position win championships.

Vancho Cirovski, my friend and client, saw the power of team chemistry on the field as an expert soccer player and in the executive suite as a VP of HR. He believes that team connectivity and communication distinguishes the great teams from the also-rans.

After experiencing success with social network analysis [SNA] in the workplace, Vancho wondered if SNA could be applied equally well to sport. His brother, Sasho, was coaching a Division I NCAA Men's Soccer team -- University of Maryland Terrapins -- that was struggling. Following a rise to a level of success the "Terps" were in a "funk", as all teams are bound to be. Could it be they had enough talent, but that the team chemistry was wrong? Sasho was willing to "think outside the box" for a solution.

Vancho and I took an organizational network survey and adapted it to team sports. We divided the questions to cover both on-field and off-the-field team chemistry. We included questions that would reveal emergent leadership on the team. To make a long story short, the year following the SNA intervention, the team that was rich in talent, now had their chemistry balanced, and the results were obvious. They won the NCAA Championship!

The full story is here. Vancho, and his brother Sasho, are written up in the current Business Week special issue on Competition -- Game Plan: First Find The Leaders

UPDATE #1: US Basketball Team Lacks "Chemistry" ends up with "Le Bronze" in World Basketball Championships. More proof that the star strategy often does not work as expected. A team loaded with NBA stars, including the great LeBron James of Cleveland, cannot beat all European teams, with no stars but lots of chemistry.

UPDATE #2: Superstar NY Yankees lose again! The team with the highest payroll, and the best hitting line-up in baseball, is eliminated early from the playoffs by the Detroit Tigers [no superstars]. Expect a big shake-up in the off season for the NY Yankees... but will it result in better chemistry???

UPDATE #3: Once again, the Yankees lose! The team with the highest payroll, and still the best hitting line-up in baseball, is eliminated early from the playoffs again -- this time by my hometown Cleveland Indians[no superstars]. The Indians payroll is 1/4 that of the Yankees. The Yankees follow a strategy that fails them in the playoffs year after year. One of our faults, as humans, is we have a difficult time unlearning -- especially those things that bring us some success but do not allow us to reach our goals.

This NY Times article explains how the Yankees have a 'decentralized' team with no strong leader. Maybe that works when things are going well, but fails them in times of adversity when a strong emergent leader may help?

Originally published on August 11, 2006

Passive Survivability

Working with Entrepreneurs for Sustainability [E4S] we are well aware of the economic benefits of sustainable systems and buildings. Now comes another benefit -- Passive Survivability. Not only are sustainable buildings an advantage for you economically, they may also help save your life after a severe weather event [cold or hot], a system failure [electric grid or gas pipeline], or a terrorist attack.

Passive survivability works with networks also -- the better your net, the more survivable you, your family, your neighborhood, your region, or your country. The right connections create resilience -- your network does not fall apart in times of failure or trauma. Weaving your network, and those of the groups you belong to, obviously helps economically but it may also make the difference of whether you survive or not.

What's the difference between a person down on their luck and
1) getting help and assistance both formally and informally, or
2) living on the street?

The person living on the street has no connections that care enough to help. The person with connections has passive survivability -- better than an insurance policy!

Where are you in the network continuity mapped above?

An isolate, connected in a small group, or in the "thick of things"?

Originally posted July 17, 2006

Blogging Patterns

Our calling patterns, our money flows... it is not surprising that next to be analyzed are our blogging patterns. Who blogs what, and who links to whom, is open source information. This data is public and available to anyone -- no court approval required. The U.S. Department of Defense recognizes this and are funding a study.

But, do terrorists blog??? Real terrorists with real plans? I doubt it -- especially after the Air Force press release above! However, people with political views and affiliations do blog.

Our blogging patterns -- who posts, who links, who comments -- are rich relational data. They reveal the social network around any blog. Also revealed are emergent communities of blogs -- usually "birds of a feather". But, the patterns reveal more than that. They are a great example of how one network reveals another network -- how public information can reveal private choices.

In a political war[the upcoming elections of 2006 and 2008?], the battling parties would like to know their opponent's structures -- how are they organized, who are the key nodes in their network, and where are their points of failure. With the no-holds-barred political strategies of today the following questions are being asked: Who do we discredit today? Where do we split the network so that it declines into ineffective fragmentation? Whose switchboard do we tie up? Who do we start rumors about? Who do we turn against each other? In other words, how do we disrupt the others from waging an effective campaign? These are all questions that can be answered beginning with link analysis of public information on the WWW. Link analysis tools and public data are available to all who desire them. Which leads to an interesting possibility... if the government is mapping the blogosphere, will the bloggers map the government?

Disrupting terrorist networks is a good thing -- we want to dismantle their networks. But is it a good thing to do with your neighbors and fellow citizens? Political polarization is an effective election strategy, but it just makes us weaker as a group to our foes. Weaving together perspectives and people here at home, and with our allies, makes us much stronger to any and all enemies.

Originally posted July 2, 2006

Listening to Conversations

Several years ago I was invited to speak on "social cartography" at the ART + COMMUNICATION conference in Riga, Latvia. Included in that conference program were performances of ambient electronic music -- some very unique, using processed signals from old Soviet radar installations that still exist in some parts of the Baltics. I was talking to one of the electronic artists and he asked "I wonder what your networks sound like? You should try to put your networks to music/sound." My hobby is electronic music, and I have several music synthesizers that I play. So, I thought "Hmmm. I'll give it a try."

This talk with the electronic musician is an example of how innovation happens when people from two diverse communities interact. Innovation happens at the intersections! Diversity is important, but similarity in perspectives/knowledge is also required. If we did not have an overlap of experience around ambient music, his comments would have seemed silly to me, and I would have quickly forgotten them. But he and I had the right mix of similarity and diversity for an idea to sprout. That is why I say...

"Connect on your similarity and profit from your diversity!"

I have yet to figure out how to model a complete network in sound, but I am starting to experiment with conversations as ambient music. Look at this brief intro to the soundscapes of conversations, including links to several ambient works of mine.

What do you think? What conversations do the three soundscapes remind you of?

Enjoy!

Originally published June 18, 2006

Entrepreneurial Networks

Entrepreneurs for Sustainability[E4S] is a NE Ohio network of entrepreneurs and change agents from business, government, academia and non-profit sectors who are implementing sustainability principles. They celebrated the Open House of their new work/meeting space this week. Included in that celebration was a network map of almost 600 NE Ohio entrepreneurs and their colleagues who run sustainable businesses in the Cleveland-Akron-Canton-Youngstown Ohio region.

As with most network maps, this one [printed wall size], soon had a crowd around it pointing, laughing, taking notes & pictures, and discussing. Several people, who did not find themselves on the map, quickly filled out a network survey form which were judiciously placed below the map. Entrepreneurs, and their support organizations, are connected on the map if they share information, advice, or ideas with each other in the execution of their business. [The map above does not contain the names of the entrepreneurs, nor their businesses.]

The three purple nodes in the center of the diagram are Holly Harlan, Courtney DeOreo, and Stephanie Strong -- the leaders of E4S. They are all excellent network weavers. Holly, the founder of E4S, and one of the top network weavers in NE Ohio, is fun to watch at a gathering as she makes one key introduction after another.

E4S is not just growing in size, it is growing in connectivity!

Originally published June 10, 2006

Needle in a Haystack

We focus on networks for good. Unfortunately, others on this planet build networks of crime and terror. These networks are soon caught in a dance of stealth vs. exposure.

A controversy arose when USA Today announced, in a front-page article, the US government's NSA was using "social network analysis" on phone records of US citizens to catch international terrorists. Some citizens were scared, others assured, while still others sounded like Alfred E Neuman -- What, me worry? Since "social network analysis" was a foreign term to most journalists, they started Googling. My phone started ringing off the hook. Soon "social network analysis" was front page news.

As I talked to the various journalists, I soon realized that they are also creators of networks, but not exactly "weavers". They make themselves the hub in a network of many spokes -- playing the "structural holes" between the spokes. Journalists survive on these trusted experts, who not only provide knowledge and opinion, but often introduce the journalists to other go-to people. It was an interesting experience. Most of my quotes were used correctly, except for one I/T publication that got it exactly the opposite of what I said. Once discovered, they were very quick and gracious in fixing their error.

The point I made to all of the journalists was that a massive who-calls-whom database by itself was not going to tell you much -- and getting more data is not the answer. The best way to use who-calls-whom data is to find an entry point into the terror network, via a suspect, and then unravel the network neighborhood around them using whatever contact data can be obtained via legal surveillance... like I wrote in 2002.

Lessons can be learned in the most unlikely places. While I was examining networks of terror, I learned quite a bit about weaving resilient networks for good. If you take something apart, you learn how it is put together, and how you can improve it.

Here are some of the better articles from my month as an instant pundit...
• Washington Post
• Cleveland Plain Dealer
• Christian Science Monitor
• Newsweek
• SLATE

Originally published June 10, 2006

The Power of Being Connected

Barbara Payne finds a study of the glaring obvious -- people in nursing homes do better when they eat together -- instead of alone in their rooms. As she says, "Well, Duh". Wayne Baker also talks about the health, happiness, and longer life implications of being embedded, and active, in healthy social networks. This is one of those dynamics that seem to pervade all mammal systems from the business world to the bovine world. Well-woven networks affect your whole life more than you may realize!

Originally published May 10, 2006