mlsanityData to 7 Oct 2026

NAYEL at SemEval-2020 Task 12: TF/IDF-Based Approach for Automatic Offensive Language Detection in Arabic Tweets

arXiv 2007.13339 ↗First posted 27 Jul 2020cs.CL cs.IRcited by 1

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Abstract (arXiv)

In this paper, we present the system submitted to "SemEval-2020 Task 12". The proposed system aims at automatically identify the Offensive Language in Arabic Tweets. A machine learning based approach has been used to design our system. We implemented a linear classifier with Stochastic Gradient Descent (SGD) as optimization algorithm. Our model reported 84.20%, 81.82% f1-score on development set and test set respectively. The best performed system and the system in the last rank reported 90.17% and 44.51% f1-score on test set respectively.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 27 Jul 2020.

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