Paper: Detecting Subgroups in Online Discussions by Modeling Positive and Negative Relations among Participants

ACL ID D12-1006
Title Detecting Subgroups in Online Discussions by Modeling Positive and Negative Relations among Participants
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2012
Authors

A mixture of positive (friendly) and nega- tive (antagonistic) relations exist among users in most social media applications. However, many such applications do not allow users to explicitly express the polarity of their interac- tions. As a result most research has either ig- nored negative links or was limited to the few domains where such relations are explicitly expressed (e.g. Epinions trust/distrust). We study text exchanged between users in online communities. We find that the polarity of the links between users can be predicted with high accuracy given the text they exchange. This allows us to build a signed network represen- tation of discussions; where every edge has a sign: positive to denote a friendly relation, or negative to denote an antagonistic relation. We also connect ou...