Marc Earls’ blog had a link to this interesting video last week.  Eric Sun from the department of Computer Science in Stanford talks about an analysis he did using data on 262,985 Facebook Pages and their associated fans.  He analyzed how information propagates through the Facebook network by looking at the popularity of fan pages. 

Sun wanted to test the hypothesis that the popularity of a page starts with a small number of important influencers who then influence their large networks.  He also tried to predict how influential a person is based on the number of friends they have, their activity levels and their demographics.

The conclusions were interesting :

It is more important to find a large population on Facebook than it is to find a small number of influentials.  The Facebook network is very connected.  Because of this, ideas with good receptiveness will attract wide, long connected clusters. 

Even if we wanted to find influentials, this would be very hard.  Sun and his team did not manage to identify influentials based on activity levels, number of friends, Facebook age or demographics.  Anyone can be an influential – it is only related to exposure. 

If you are interested in the topic, the video is definitely worth 20 minutes of your time. 

Also, the quants among you should check out other videos on the videolectures site.  It’s a great resource if you want to brush up on your math skills.

I’m going to bet that the Portable Social Graph is going to be the next big thing in social marketing.

The idea of the plain old social graph has been around for several years. Basically, this term refers to the representation of our relationships on the web. The graph has long been recognized as valuable information, both for the owner (you and me) and for social networks.

The problem has always been that you have to replicate it on many different sites. Two years ago an influential article by Brad Fitzgerald, a programmer, proposed that you should be able to move your graph around the web with you.

Now the idea of the Portable Social Graph has really taken off. In May, web guru Jeffrey Rayport, writing in Business Week said that:

“…new tools will allow members to take their social-media identities with them when they go to other Web sites. Once wedded to a single networking platform, a member’s “social graph” password, profile, list of friends is becoming portable. In other words, as they surf the Web, users increasingly will be able to define themselves by their social network of origin.

That’s big. It signals that Web companies are no longer in a race to build “destination sites” that attract vast numbers of users. Instead, social networking players are racing to extend their influence over the entire Web by exporting their social features to all sites.”

An article in this month’s Wired magazine explains how central this is to Facebooks’ plan for web dominance:

“Facebook CEO Mark Zuckerberg envisions a more personalized, humanized Web, where our network of friends, colleagues, peers, and family is our primary source of information, just as it is offline. In Zuckerberg’s vision, users will query this “social graph” to find a doctor, the best camera, or someone to hire—rather than tapping the cold mathematics of a Google search. “

Facebook has already taken two big steps towards achieving this vision. Facebook Connect, launched in December 2008, is a network of more than ten thousand independent sites that allows Facebook users to use their friend’s details. So you can go to Delicious and see what your friends bookmarked or go to CNN and see what stories they read. In April, Facebook launched Open Stream API, which allows you to see friends’ newsfeeds from any site, not just Facebook. To understand the full significance of this for marketers, you should take a look at a presentation that Shiv Singh of Razorfish made in December of last year. He speculates about what could happen when Facebook Connnect is linked to Amazon or iTunes, for example. You can now get friends’ recommendations right at the point of purchase. All of this works, of course, because friends are the most trusted and sought after sources of advice on just about everything, as countless surveys have shown us. What does this mean for us? Firstly it vindicates what Mark Earls has been saying with his “herd” theory for some time now. It means that our targeting should be aimed much more towards social groups than individuals. It also means we should turn our web analytics away from the sites and towards the individuals that use them. They are going to be keepers of their own graphs. We should make friends with them quickly! More specifically, we should target those not only with the largest social graphs, but the most active. The key is probably to find those with the greatest inner circles - friends they are close to and contact frequently. How do we measure that?

Dimitri posted last week on IBM’s new fascinating new software Many Eyes. This is an open site that allows you to bring your own data and use IBM’s state-of-the-art visualization tools to bring them to life. (The uses to which people have put them make a telling story of the arcane interests of those in the data visualization cult!)

One of my favorite groups is visualizations by amateur biblical scholars that chart the connections between different figures in the New Testament. The illustration above is a good example.

I’m interested in this because it’s a great example of The Ecosystem of Influence, which I’ve talked about before in connection with Facebook.

In the illustration above, Jesus is, as you’d expect the centre of the ecosystem, but you can quickly read the other major figures and the patterns of interaction.

In this example, you can click on different figures to isolate their patterns of influence in a different color. (Click on Jesus, and the web lights up like a Christmas tree!) You can even drag and click the different figures to shape the web differently.

This is a very useful tool for the new PR, which our colleague John Bell talks about extensively in his blog, The Digital Influence Mapping Project. In the old PR, influence worked top down. You would have tried to secure the endorsement of Jesus and leave it at that. In the new world, you can build up from a variety of different influencers. In the 2003 book, The Influentials, this is described by authors Jon Berry and Ed Keller as moving from the “era of deference to the era of influence”.

Amid all the bleak forecasts about Swine Flu, it’s timely (and far less worrying) to reflect once more on the role epidemics play in marketing.

This subject, was first popularized in Malcolm Gladwell’s The Tipping Point, a book which like its subject, has spawned a thousand virulent mutations. 

My friend Lisa Flattery recently alerted me to a superbly documented example of a social epidemic, in an article by Chris Wilson in Slate. 

Wilson polled his readers on when they first encountered a “25 Things” note on Facebook.  If you’re on Facebook, you can’t have escaped this phenomenon at the beginning of the year.  It’s a sort of mini-profile made through a list of personal idiosyncrasies.  It seemed to explode over a couple of weeks and then disappear altogether.  Wilson wanted to find out why. 

He notes that “’25 Things’ wasn’t always ‘25 Things’”.  It stated as a chain letter called “16 Random Things You Know About Me”.  Similar lists had appeared on Friendster, My Space and other sites.  Wilson continues:

“Like any disease, “Random Things” was mutating in hopes of finding a strain uniquely suited to its host.  In this case, the right number was vital to its survival:  The more people who are tagged, the more likely the note is to spread.”  The list eventually stabilized at “25 Things”.  It then spread rapidly, starting on January 20^th and fizzling out towards the end of the month.

I think that there are three big lessons from this case for marketers.

Firstly, it shows the importance of recency.  There’s a graph in the article that shows the date that users first wrote their own notes, after being tagged by someone else.  17 percent of people did it the same day, the median is three days and there is a sharp decay from there.  Lauren Ancel Meyers, a specialist in infectious diseases at the University of Texas, likens this to radioactive decay.  We’ve seen this elsewhere.  If credit card holders don’t activate within 90 days of receiving the card, they won’t activate at all.

Second is the importance of mutation.  “25 Things” would never have taken off at all if it hadn’t been allowed to find it’s most successful form.  In a world of ‘open source marketing’, customers have to be allowed to ‘play’ with brands and reinvent them to their own ends.

Thirdly, fads are fads.  They do mutate, but when successful, they quickly run out of people to infect.  As Wilson says:  “All in all, Facebook infections look remarkably similar to human ones.  And like organisms, the odds do seem stacked against all but the fittest of memes”. 

Hopefully, swine flu will turn out to be a fad too. 

As you will have surely heard, Facebook recently acquired its 200 millionth user.  It has achieved this in under five years, doubling in size in the last 8 months alone. 

This has produced a lot of commentary.  Since there is so much data surrounding people’s interactions with Facebook, it can be examined in all sorts of social studies.

One in particular caught my eye last week.  The New York Times article had a sidebar produced by Facebook’s analysts, which is a wonderful piece of data visualization. 

There are two parts.  The first shows the global expansion, in a series of step changes precipitated by changes in the rules of who could join.  It plots this against the average age distribution of the members.  Facebook famously started at Harvard in February 2004 and quickly expanded to other universities, and you can see that initially all the members are 18-24 in the first graph.  In 2005, it expanded to include most American colleges and high schools.  In February 2006 it allowed anyone to join, and the age profile increased.  By February 2007, it had reached 50 million members.  By February 2008 Facebook is translated into more than 40 languages.  Growth is fastest among those over 35. 

For me, the second set of diagrams is the most fascinating.  This is a real life example of what I’ve been calling ‘The Ecosystem of Influence’.  It illustrates the Facebook network of one employee.  The friends are dots, and the interactions are lines between the dots.  It looks like an airline route map. 

The point of the diagrams is that this individual has four networks of different sizes, defined by different levels of social intimacy.  He has 178 friends in total.  But he reads the postings of a much smaller group, and sends messages to a much smaller group yet again (“one way pings”).  And of these only some reply.  Without counting the lines, this looks like maybe 15