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This work investigates style and topic aspects of language in onlinecommunities: looking at both utility as an identifier of the community andcorrelation with community reception of content. Style is characterized using ahybrid word and part-of-speech tag n-gram language model, while topic isrepresented using Latent Dirichlet Allocation. Experiments with several Redditforums show that style is a better indicator of community identity than topic,even for communities organized around specific topics. Further, there is apositive correlation between the community reception to a contribution and thestyle similarity to that community, but not so for topic similarity.

Characterizing the Language of Online Communities and its Relation to Community Reception