Revue d'Information Scientifique et Technique

A logistic regression algorithm for Arabic hate speech detection

Arabic language is one of the most popular languages and it is widely used in social media networks. During the pandemics, the spread of fake news, rumors, hate speech and spams increased dramatically which makes the detection of
the misinformation sources very important and very helpful to control the situation. A lot of Arabic natural language processing (ANLP) works are proposed in the literature to solve such problems, in this paper we propose a time efficient and high precision and accuracy algorithm for Arabic Hate speech detection.
A classical Machine Learning (ML) logistic regression algorithm is 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.

Auteurs : Abdelmounim Sellidj


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