Data di Pubblicazione:
2021
Abstract:
n this paper we describe the Hate and Morality (HaMor) submission for the Profiling Hate Speech Spreaders on Twitter task at PAN 2021. We ranked as the 19th position - over 66 participating teams - according to the averaged accuracy value of 73% reached by our proposed models over the two languages. We obtained the 43th higher accuracy for English (62%) and the 2nd higher accuracy for Spanish (84%).
We proposed four types of features for inferring users attitudes just from the text in their messages: HS detection, users morality, named entities, and communicative behaviour. The results of our experiments are promising and will lead to future investigations of these features in a finer grained perspective.
Tipologia CRIS:
04A-Conference paper in volume
Elenco autori:
mirko lai, marco antonio stranisci, cristina bosco, rossana damiano, viviana patti
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Link al Full Text:
Titolo del libro:
Proceedings of the Working Notes of CLEF 2021 - Conference and Labs of the Evaluation Forum
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