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Dr. Hamada Ali Mohamed Ali Nayel :: Publications: |
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| Title: | NAYEL at SemEval-2020 Task 12: TF/IDF-Based Approach for
Automatic Offensive Language Detection in Arabic Tweets |
| Authors: | Hamada A. Nayel |
| Year: | 2020 |
| Keywords: | Offensive language detection; Arabic NLP, Social Media Analysis |
| Journal: | Proceedings of the Fourteenth Workshop on Semantic Evaluation |
| Volume: | 2020 |
| Issue: | Not Available |
| Pages: | 2086–2089 |
| Publisher: | International Committee for Computational Linguistics |
| Local/International: | International |
| Paper Link: | |
| Full paper | Not Available |
| Supplementary materials | Not Available |
| 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. |
