Staff Members - Benha University
NAYEL at SemEval-2020 Task 12: TF/IDF-Based Approach for Automatic Offensive Language Detection in Arabic Tweets
Proceedings of the Fourteenth Workshop on Semantic Evaluation • 2020
Publication Information
Authors
Hamada A. Nayel
Keywords
Offensive language detection; Arabic NLP, Social Media Analysis
Journal
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Publisher
International Committee for Computational Linguistics
Volume
2020
Issue
Not Available
Pages
2086–2089
publication.type
International
Paper Link
Open Link
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.