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.

HaMor at the Profiling Hate Speech Spreaders on Twitter

mirko lai
Co-first
;
marco antonio stranisci
Co-first
;
cristina bosco;rossana damiano;viviana patti
Last
2021-01-01

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.
Working Notes of CLEF 2021 - Conference and Labs of the Evaluation Forum
Bucharest, Romania
22/09/2021
Proceedings of the Working Notes of CLEF 2021 - Conference and Labs of the Evaluation Forum
CEUR Workshop Proceedings
2936
2047
2055
http://ceur-ws.org/Vol-2936/paper-178.pdf
mirko lai, marco antonio stranisci, cristina bosco, rossana damiano, viviana patti
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1802081
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