Work

HaMor at the Profiling Hate Speech Spreaders on Twitter

Year: 2021

Type: conference-paper

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.

Source: Institutional Research Information System University of Turin (University of Turin)

Authors: Mirko Lai, Marco Antonio Stranisci, Cristina Bosco, Rossana Damiano, Viviana Patti

Institutions: University of Turin, University of Cagliari, University of Groningen

Language: English

Topic: Hate Speech and Cyberbullying Detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W3198170062

FWCI: 0.187

Cites: 8

Cited by: 2

Related to: 10