An Italian lexical resource for incivility detection in online discourses

Alice Tontodimamma (), Lara Fontanella (), Stefano Anzani () and Valerio Basile ()
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Alice Tontodimamma: G. d’Annunzio University of Chieti-Pescara
Lara Fontanella: G. d’Annunzio University of Chieti-Pescara
Stefano Anzani: G. d’Annunzio University of Chieti-Pescara
Valerio Basile: University of Turin

Quality & Quantity: International Journal of Methodology, 2023, vol. 57, issue 4, No 4, 3019-3037

Abstract: Abstract The exponential growth of social media has brought an increasing propagation of online hostile communication and vitriolic discourses, and social media have become a fertile ground for heated discussions that frequently result in the use of insulting and offensive language. Lexical resources containing specific negative words have been widely employed to detect uncivil communication. This paper describes the development and implementation of an innovative resource, namely the Revised HurtLex Lexicon, in which every headword is annotated with an offensiveness level score. The starting point is HurtLex, a multilingual lexicon of hate words. Concentrating on the Italian entries, we revised the terms in HurtLex and derived an offensive score for each lexical item by applying an Item Response Theory model to the ratings provided by a large number of annotators. This resource can be used as part of a lexicon-based approach to track offensive and hateful content. Our work comprises an evaluation of the Revised HurtLex lexicon.

Keywords: Uncivil speech detection; Lexicon-based approach; Sentiment analysis; Item response theory model; Raters’ consistency; 91F20; 62H25 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11135-022-01494-7

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