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

• URL: http://arxiv.org/abs/2007.13339v1
• Date: Mon, 27 Jul 2020 07:44:00 GMT
• Title: NAYEL at SemEval-2020 Task 12: TF/IDF-Based Approach for Automatic Offensive Language Detection in Arabic Tweets
• Authors: Hamada A. Nayel
• Abstract summary: The proposed system aims to automatically identify the Offensive Language in Arabic Tweets. A machine learning based approach has been used to design our system. The best performed system and the system in the last rank reported 90.17% and 44.51% f1-score on test set respectively.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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