Work

The Role of Computational Stylometry in Identifying (Misogynistic) Aggression in English Social Media Texts

Year: 2020

Type: conference-paper

Abstract: In this paper, we describe UniOr ExpSys team participation in TRAC-2 (Trolling, Aggression and Cyberbullying) shared task, a workshop organized as part of LREC 2020. TRAC-2 shared task is organized in two sub-tasks: Aggression Identification (a 3-way classification between “Overtly Aggressive”, “Covertly Aggressive” and “Non-aggressive” text data) and Misogynistic Aggression Identification (a binary classifier for classifying the texts as “gendered” or “non-gendered”). Our approach is based on linguistic rules,stylistic features extraction through stylometric analysis and Sequential Minimal Optimization algorithm in building the two classifiers.

Source: ARCHIVIO ISTITUZIONALE DELLA RICERCA-UNIVERSITA DEGLI STUDI DI NAPOLI "LORIENTALE"

Authors: Antonio Pascucci, Raffaele Manna, Vincenzo Masucci, Johanna Monti

Language: English

Topic: Hate Speech and Cyberbullying Detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Gender equality

Open Access status: green

Funder: Università degli Studi di Napoli Federico II

OpenAlex ID: W3030082272

FWCI: 0.286

Cites: 37

Cited by: 4

Related to: 10