OffendES: A New Corpus in Spanish for Offensive Language Research

Flor Miriam Plaza-del-Arco, Arturo Montejo-Ráez, L. Alfonso Ureña-López, María-Teresa Martín-Valdivia


Abstract
Offensive language detection and analysis has become a major area of research in Natural Language Processing. The freedom of participation in social media has exposed online users to posts designed to denigrate, insult or hurt them according to gender, race, religion, ideology, or other personal characteristics. Focusing on young influencers from the well-known social platforms of Twitter, Instagram, and YouTube, we have collected a corpus composed of 47,128 Spanish comments manually labeled on offensive pre-defined categories. A subset of the corpus attaches a degree of confidence to each label, so both multi-class classification and multi-output regression studies are possible. In this paper, we introduce the corpus, discuss its building process, novelties, and some preliminary experiments with it to serve as a baseline for the research community.
Anthology ID:
2021.ranlp-1.123
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
Month:
September
Year:
2021
Address:
Held Online
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
1096–1108
Language:
URL:
https://aclanthology.org/2021.ranlp-1.123
DOI:
Bibkey:
Cite (ACL):
Flor Miriam Plaza-del-Arco, Arturo Montejo-Ráez, L. Alfonso Ureña-López, and María-Teresa Martín-Valdivia. 2021. OffendES: A New Corpus in Spanish for Offensive Language Research. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), pages 1096–1108, Held Online. INCOMA Ltd..
Cite (Informal):
OffendES: A New Corpus in Spanish for Offensive Language Research (Plaza-del-Arco et al., RANLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.ranlp-1.123.pdf