Proceedings of the Annual Meeting of the Cognitive Science Society

Ostracism is a social phenomenon, shared by most social animals, including humans. Its detection plays a crucial role forthe individual, with possible evolutionary consequences for the species.Considering (1) its relation with communication and therefore language and (2) its social nature, we hypothesised that thecombination of linguistic and community-level social features would have a positive impact on the automatic recognitionof ostracism in human online communities.We modelled a linguistic community through Reddit data and we analysed the performance of simple classification al-gorithms (Nave Bayes and SVM), particularly focusing on the feature selection. Comparing the accuracy scores of thealgorithms fed with a) linguistic features, b) extralinguistic features, and c) linguistic + extralinguistic features, we testedour hypothesis, showing how models based on c) generally outperform.To our knowledge, this is the first attempt to automatise the identification of such a complex phenomenon through NLPtechniques.