document: User grouping behavior in online forums Online forums represent one type of social media that is particularly rich for studying human behavior in information seeking and diffusing . The way users join communities is a reflection of the changing and expanding of their interests toward information . In this paper , we study the patterns of user participation behavior , and the feature factors that influence such behavior on different forum datasets . We find that , despite the relative randomness and lesser commitment of structural relationships in online forums , users ' community joining behaviors display some strong regularities . One particularly interesting observation is that the very weak relationships between users defined by online replies have similar diffusion curves as those of real friendships or co-authorships . We build social selection models , Bipartite Markov Random Field ( BiMRF ) , to quantitatively evaluate the prediction performance of those feature factors and their relationships . Using these models , we show that some features carry supplementary information , and the effectiveness of different features vary in different types of forums . Moreover , the results of BiMRF with two-star configurations suggest that the feature of user similarity defined by frequency of communication or number of common friends is inadequate to predict grouping behavior , but adding node-level features can improve the fit of the model .
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