Analysing Moral Beliefs for Detecting Hate Speech Spreaders on Twitter
Published in Proceedings of the 13th International Conference of the CLEF Association, CLEF 2022, 2022
Recommended citation: Mirko Lai, Marco Antonio Stranisci, Cristina Bosco, Rossana Damiano, and Viviana Patti. 2022. Analysing Moral Beliefs for Detecting Hate Speech Spreaders on Twitter. In Experimental IR Meets Multilinguality, Multimodality, and Interaction: 13th International Conference of the CLEF Association, CLEF 2022, Bologna, Italy, Proceedings (pp. 149-161). Cham: Springer International Publishing https://link.springer.com/chapter/10.1007/978-3-031-13643-6_12
The Hate and Morality (HAMOR) submission for the Profiling Hate Speech Spreaders on Twitter task at PAN 2021 ranked as the 19th position - over 67 participating teams - according to the averaged accuracy value of 73% over the two languages - English (62%) and Spanish (84%). The method 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
Recommended citation: Mirko Lai, Marco Antonio Stranisci, Cristina Bosco, Rossana Damiano, and Viviana Patti. 2022. Analysing Moral Beliefs for Detecting Hate Speech Spreaders on Twitter. In Experimental IR Meets Multilinguality, Multimodality, and Interaction: 13th International Conference of the CLEF Association, CLEF 2022, Bologna, Italy, Proceedings (pp. 149-161). Cham: Springer International Publishing