NAYEL at SemEval-2020 Task 12: TF/IDF-Based Approach for Automatic Offensive Language Detection in Arabic Tweets
Computation and Language
2020-07-28 v1 Information Retrieval
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.
Keywords
Cite
@article{arxiv.2007.13339,
title = {NAYEL at SemEval-2020 Task 12: TF/IDF-Based Approach for Automatic Offensive Language Detection in Arabic Tweets},
author = {Hamada A. Nayel},
journal= {arXiv preprint arXiv:2007.13339},
year = {2020}
}
Comments
Working notes of NAYEL's team submission to task 12 at SemEval-2020