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SmartData Collective > Uncategorized > The Real Twitter
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The Real Twitter

Daniel Tunkelang
Last updated: 2009/01/07 at 5:12 AM
Daniel Tunkelang
5 Min Read
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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 N…

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.

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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.

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Daniel Tunkelang January 7, 2009
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