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

Antonio Pascucci, Raffaele Manna, Vincenzo Masucci, Johanna Monti


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.
Anthology ID:
2020.trac-1.11
Volume:
Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Ritesh Kumar, Atul Kr. Ojha, Bornini Lahiri, Marcos Zampieri, Shervin Malmasi, Vanessa Murdock, Daniel Kadar
Venue:
TRAC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
69–75
Language:
English
URL:
https://aclanthology.org/2020.trac-1.11
DOI:
Bibkey:
Cite (ACL):
Antonio Pascucci, Raffaele Manna, Vincenzo Masucci, and Johanna Monti. 2020. The Role of Computational Stylometry in Identifying (Misogynistic) Aggression in English Social Media Texts. In Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying, pages 69–75, Marseille, France. European Language Resources Association (ELRA).
Cite (Informal):
The Role of Computational Stylometry in Identifying (Misogynistic) Aggression in English Social Media Texts (Pascucci et al., TRAC 2020)
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PDF:
https://aclanthology.org/2020.trac-1.11.pdf