INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive Text

Sabino Miranda-Jiménez, Eric S. Tellez, Mario Graff, Daniela Moctezuma


Abstract
This paper describes our participation in OffensEval challenges for English, Arabic, Danish, Turkish, and Greek languages. We used several approaches, such as μTC, TextCategorization, and EvoMSA. Best results were achieved with EvoMSA, which is a multilingual and domain-independent architecture that combines the prediction from different knowledge sources to solve text classification problems.
Anthology ID:
2020.semeval-1.262
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Venue:
SemEval
SIGs:
SIGLEX | SIGSEM
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
1992–1997
Language:
URL:
https://aclanthology.org/2020.semeval-1.262
DOI:
10.18653/v1/2020.semeval-1.262
Bibkey:
Cite (ACL):
Sabino Miranda-Jiménez, Eric S. Tellez, Mario Graff, and Daniela Moctezuma. 2020. INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive Text. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1992–1997, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive Text (Miranda-Jiménez et al., SemEval 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2020.semeval-1.262.pdf