Abstract
Offensive language is a common issue on social media platforms nowadays. In an effort to address this issue, the SemEval 2020 event held the OffensEval 2020 shared task where the participants were challenged to develop systems that identify and classify offensive language in tweets. In this paper, we present a system that uses an Ensemble model stacking a BOW model and a CNN model that led us to place 29th in the ranking for English sub-task A.
Cite
CITATION STYLE
Boriola, M. A. H., & Paetzold, G. H. (2020). UTFPR at SemEval 2020 Task 12: Identifying Offensive Tweets with Lightweight Ensembles. In 14th International Workshops on Semantic Evaluation, SemEval 2020 - co-located 28th International Conference on Computational Linguistics, COLING 2020, Proceedings (pp. 2232–2236). International Committee for Computational Linguistics. https://doi.org/10.18653/v1/2020.semeval-1.297
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