Twitter Friends and the Influence of Influentials in Word of Mouth Marketing

January 16, 2009

Social Networks that Matter

Without going into links to specific posts, I’ve noticed a trend among many blogs I try to keep up with over the past couple of years. I can’t count the number of times I’ve seen prominent bloggers post publicly about having to pare down the list of RSS feeds they read, or tweets they respond to. Since Peter Kim’s blog is the most recent instance of the trend I’ll use one of his recent posts as an example of what I mean. Peter noted that he increasingly hears an echo chamber across social media blogs in which the same content, case studies, anecdotes, etc. gets repeatedly posted and commented on. More cynical observers might contend that the complaints about information overload from influentials is a little like strutting in front of a crowd. Nevertheless, it is difficult to dispute the point that attention is a scarce resource on the Web. So is engagement.

Ross Mayfield recently pointed to a study published by researchers at the Social Computing Lab of HP Laboratories that addresses the point succinctly by pointing to constraints on friendship in directed social networks such as Twitter. A directed social network is characterized by an absence of explicit reciprocity constraints, fifty people can follow one person without that person necessarily following any of them. First Monday’s most recent issue includes an article, Social Networks that Matter: Twitter under a Microscope, that reports on a study of Twitter users by Bernardo A. Huberman, Daniel M. Romero, and Fang Wu of HP Laboratories.

The authors analyzed data from 309,740 people using Twitter. They compared the network of interactions people actually engage in while using social computing technologies such as Twitter to the network of connections with whom one shares a social relationship. Networks of actual interaction are considered networks that matter by the authors.

By networks that matter we mean those networks that are made out of the pattern of interactions that people have with their friends or acquaintances, rather than constructed from a list of all the contacts they may decide to declare.

In other words, the research focused on reciprocity as well as connection in studying the social network of Twitter. 
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