Revue de l'Information Scientifique et Technique
Volume 27, Numéro 2, Pages 44-49
2023-11-08
A Logistic Regression Algorithm For Arabic Hate Speech Detection
Authors : Sellidj Abdelmounim .
Abstract
Arabic language is one of the most popular languages and it is widely used in social media networks. In pandemics the spread of fake news, rumors, hate speech and spams increase dramatically which makes the detection of the misinformation sources is very important and vary helpful to control the situation. A lot of Arabic naturel language processing (ANLP) works are proposed in literature to solve such problems, in this paper we propose a time efficient and high precision and accuracy algorithm. A classical Machine Learning (ML) logistic regression algorithm used in this ANLP work to detect hate speech, the data of this work are collected from Twitter social media during the COVID-19 pandemic, we use 80% of the data to train our algorithm and 20% of data to test it. The proposed algorithm has high accuracy and precision in the tested comments (a precision of 88.77% an accuracy of 98.48%). This work shows that, the classical ML algorithms have good performances in such problems.
Keywords
hate speech detection ; logistic regression ; Arabic NLP (ANLP) ; naturel language processing (NLP) ; Arabic hate speech detection
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