471 citations · 1.3k across the 58 of their papers we have counts for
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Stochastic Models Predict User Behavior in Social Media
Tad Hogg, Kristina Lerman, Laura M. Smith
User response to contributed content in online social media depends on many factors. These include how the site lays out new content, how frequently the user visits the site, how m…
Social Dynamics of Digg
Tad Hogg, Kristina Lerman
Online social media provide multiple ways to find interesting content. One important method is highlighting content recommended by user's friends. We examine this process on one su…
Using Stochastic Models to Describe and Predict Social Dynamics of Web Users
Kristina Lerman, Tad Hogg
Popularity of content in social media is unequally distributed, with some items receiving a disproportionate share of attention from users. Predicting which newly-submitted items w…
Using a Model of Social Dynamics to Predict Popularity of News
Kristina Lerman, Tad Hogg
Popularity of content in social media is unequally distributed, with some items receiving a disproportionate share of attention from users. Predicting which newly-submitted items w…
Stochastic Models of User-Contributory Web Sites
Tad Hogg, Kristina Lerman
We describe a general stochastic processes-based approach to modeling user-contributory web sites, where users create, rate and share content. These models describe aggregate measu…
Diversity of Online Community Activities
Tad Hogg, Gabor Szabo
Web sites where users create and rate content as well as form networks with other users display long-tailed distributions in many aspects of behavior. Using behavior on one such co…