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Model of emotional dialogues based on entropy model

Julian Sienkiewicz, Marcin Skowron, Georgios Paltoglou, Janusz Holyst

We process emotionally annotated (negative, neutral, positive) data from Internet Relay Chat (IRC) extracting 90.000 one-to-one dialogues between users. Statistical analysis shows that, regardless of the length of the dialogue measured in the number of comments, each dialogue ends when the probabilities of finding positive and neutral emotional value equalize. Moreover, the entropy of the emotional probabilities distribution increases with the dialogue evolution. Additionally we observe clustering of comments with the same emotional value. Basing on entropy growth and emotional clustering, we construct a model of dialogues that reproduces the characteristics of the real data and we show how it can be useful for an automatic moderator in this medium.

Keywords: online communication, social norms, modelling, Publications List Interact

Citation: In the Proceedings of European Conference on Complex Systems, ECCS 2011