Ostracism is a community-level phenomenon, shared by most social animals, including humans. Its detection plays a crucial role for the individual, with possible evolutionary consequences for the species. Considering (1) its bound with communication and (2) its social nature, we hypothesise the combination of (a) linguistic and (b) community-level features to have a positive impact on the automatic recognition of ostracism in human online communities. We model an English linguistic community through Reddit data and we analyse the performance of simple classification algorithms. We show how models based on the combination of (a) and (b) generally outperform the same architectures when fed by (a) or (b) in isolation.
Predicting Social Exclusion: A Study of Linguistic Ostracism in Social Networks / Gandolfi, Greta; Strapparava, Carlo. - 2769:(2020). (Intervento presentato al convegno Seventh Italian Conference on Computational Linguistics (CLiC-it 2020) tenutosi a Bologna, Italy nel March 1-3, 2021).
Predicting Social Exclusion: A Study of Linguistic Ostracism in Social Networks
Carlo Strapparava
2020-01-01
Abstract
Ostracism is a community-level phenomenon, shared by most social animals, including humans. Its detection plays a crucial role for the individual, with possible evolutionary consequences for the species. Considering (1) its bound with communication and (2) its social nature, we hypothesise the combination of (a) linguistic and (b) community-level features to have a positive impact on the automatic recognition of ostracism in human online communities. We model an English linguistic community through Reddit data and we analyse the performance of simple classification algorithms. We show how models based on the combination of (a) and (b) generally outperform the same architectures when fed by (a) or (b) in isolation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione