Author: Daniel Tunkelang

A few weeks ago, there was a flame war about Twitter authority, and I was all too eager to throw fuel on the pyre. But now that the blogosphere has calmed down a bit, I’d like to propose a ranking measure that I think might work. My apologies if it isn’t original. In fact, if you’ve seen it elsewhere, please point me to it.

Let me start with the assumptions about the model:

• Influence(X) = Expected number of people who will read a tweet that X tweets, including all retweets of that tweet. For simplicity, we assume that, if a person reads the same message twice (because of retweets), both readings count.
• If X is a member of Followers(Y), then there is a 1/||Following(X)|| probability that X will read a tweet posted by Y, where Following(X) is the set of people that X follows.
• If X reads a tweet from Y, there’s a constant probability p that X will retweet it.

This model is obviously simplistic in all three assumptions. But I think it’s a reasonable first cut. In particular, it accounts for the inflation that occurs from people who follow in the hopes of reciprocity. There’s less value in being followed by someone who follows a lot of people, because that person is less likely to read your messages or retweet them.

Of course, there’s room for adding more realism to this model, but I hope it is at least close enough to the truth to be interesting.

From this model, it’s easy to measure someone’s influence recursively, assuming that we know the constant retweet probability p:

The recursion is infinite over a graph with directed cycles, but rapidly converges as high powers of p approach zero. I would think this measure wouldn’t be hard to compute to a reasonable accuracy.

This measure strikes me as a PageRank for Twitter or any system with similar properties. There’s more room for nuance, but I at least find this approach more plausible than the ones I’ve seen. It also strikes me as hard to game, since it isn’t counting retweets, and it’s hard to add much influence through followers who don’t have any influence themselves.

What do folks think? Has anyone tried this? If not, is there anyone who’d like to try hacking an application to compute it? Either way, please let me know!

As I hope I’ve made abundantly clear in the past, this is not a corporate blog, and I try to avoid even the appearance of being a shill for my employer, our customers, or our partners.

But I hope you will understand that, in this case, it’s personal.

A couple of months ago, SLI Systems CEO Shaun Ryan did something which I thought was, to put it generously, not taking the high road. In the guise of sending out a helpful “note of caution” to SLI’s customers and prospects, he proceeded to make an attack of the kind I typically associate with desperate political campaigns.

The intended target was Endeca partner Thanx Media. But here’s where we get to the personal part. He used this post of mine to suggest that the software I’ve helped develop and deploy was difficult to set up.

At the time, I was persuaded by colleagues to take the high road myself and not respond. But now that Thanx Media has announced its latest successes, including displacing SLI at CableOrganizer.com only weeks after Ryan blogged about it, I feel it is appropriate to thank the guys at Thanx Media for defending my honor along with their own.

I’m all for healthy competition. I recently gave a technical talk at Google, whose enterprise division competes with Endeca, and I even invited a former EVP at FAST to attend. My aim in organizing the SIGIR Industry Track is to raise the caliber of discussion among competitors. I try to give credit to competitors for their successes, but more importantly I try to keep my criticism fair. I also open up my blog to comments, which means that you folks can keep me honest if I stray from the path.

Here in the United States, many of us are hopeful for an era that will bring us a new kind of politics. Why don’t we start by practicing it ourselves?

In a brilliant marketing campaign, Burger King is offering a coupon for a free Whopper to anyone who “sacrifices” ten of their Facebook friends. The “whopper sacrifice” campaign is earning mass media coverage, including in the New York Times. I checked it out myself and took the opportunity to trade ten of my more questionable online friendships for a slightly less questionable repast.

Of course, the interesting question in the context of much of the discussion on this blog is what such a campaign tells us about the value of online social network connections. On Facebook, friendship is symmetric, as is also the case on LinkedIn. But it’s interesting to consider how such a campaign might have worked on Twitter. Would you be asked to sacrifice followers or followees?

On one hand, you choose whom you follow, and in theory you follow them because you’re interested in what they have to say. It stands to reason that unfollowing someone would be a sacrifice.

On the other hand, having lots of followers is signals status and perhaps even authority. So perhaps it’s giving up followers that would be a sacrifice.

Of course, these two possibilities aren’t mutually exclusive: there may be value both in following and being followed. Regardless of whether it is better to give than receive, it may be good to do both.

Nonetheless, I suspect that the average online “friendship” is worth less than $0.37 (a whopper goes for $3.69). I’m sure Burger King will have no trouble giving away whoppers.

I just came back from the monthly NY Tech Meetup, whose theme this evening was “Built on Twitter“. While the meeting was well organized (a testament to Nate Westheimer, who received the torch from Meetup CEO Scott Heiferman, I had mixed feelings about the demos. Everyone is capitalizing on Twitter’s buzz, but so few people seem to be creating anything valuable on top of it.

But, by luck, Daniel Lemire sent me a link to Sylvie Noël’s post about a paper by HP Labs on “Twitter: Social Networks that Matter: Twitter under the microscope” by Bernardo A. Huberman, Daniel M. Romero and Fang Wu. She also pointed to an executive summary by Forrester analyst Jeremiah Owyang.

The paper is insightful. The authors practically had me at hello–this is the paper’s third paragraph:

While the standard definition of a social network embodies the notion of all the people with whom one shares a social relationship, in reality people interact with very few of those “listed” as part of their network. One important reason behind this fact is that attention is the scarce resource in the age of the web. Users faced with many daily tasks and large number of social links default to interacting with those few that matter and that reciprocate their attention. For example, a recent study of Facebook showed that users only poke and message a small number of people while they have a large number of declared friends. And a casual search through recent calls made through any mobile phone usually reveals that a small percentage of the contacts stored in the phone are frequently contacted by the user.

They then define a user’s “friend” as a person to whom that user has specifically directed at least two posts and show that the a user’s number of friends is a better predictor of the user’s activity (number of posts) than the user’s number of followers. Having thus validated the number of friends as a more important input variable than the number of followers, they explore the friend graph, which turns out to be much sparser than the follower graph.

Their conclusion:

Many people, including scholars, advertisers and political activists, see online social networks as an opportunity to study the propagation of ideas, the formation of social bonds and viral marketing, among others. This view should be tempered by our findings that a link between any two people does not necessarily imply an interaction between them. As we showed in the case of Twitter, most of the links declared within Twitter were meaningless from an interaction point of view. Thus the need to find the hidden social network; the one that matters when trying to rely on word of mouth to spread an idea, a belief, or a trend.

I urge you to read the whole paper, as my abbreviated version hardly does it justice. And then, if you’re practically minded, think about ways to build applications on Twitter than leverage this real social network that is hidden in plain sight.

I further suspect that the authors result generalize beyond Twitter to other social networks where the cost of connecting is far lower than the cost of actually investing in the connection. It doesn’t seem hard to identify the hidden social network, and by doing so we can unlock its value.

Of course, Twitter has the virtue that its network is mostly available to the public, not hidden behind a walled garden like LinkedIn or Facebook. As a result, I expect that Twitter will drive both research and innovation in the social network space, at least in the near term.