Determining Influential Users in Internet Social Networks
University of Maryland - Robert H. Smith School of Business
Anand V. Bodapati
University of California, Los Angeles (UCLA) - Anderson School of Management
Randolph E. Bucklin
UCLA Anderson School of Management
April 20, 2009
The success of Internet social networking sites depends on the number and activity levels of their user members. While users typically have numerous connections to other site members (i.e., “friends”), only a fraction of those “friends” may actually influence a member’s site usage. Since the influence of potentially hundreds of friends needs to be evaluated for each user, inferring precisely who is influential - and therefore of managerial interest for advertising targeting and retention efforts - is difficult. We develop an approach to determine which users have significant effects on the activities of others using the longitudinal records of members’ login activity. We propose a non-standard form of Bayesian shrinkage implemented in a Poisson regression. Instead of shrinking across panelists, strength is pooled across variables within the model for each user. The approach identifies the specific users who most influence others’ activity and does so considerably better than simpler alternatives. For the social networking site data, we find that, on average, about one-fifth of a user's friends actually influence his/her activity level on the site.
Number of Pages in PDF File: 44
Keywords: Internet, Social Networking, Bayesian Methods
JEL Classification: C11working papers series
Date posted: September 29, 2009
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