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All Journal International Journal of Electrical and Computer Engineering
Hossam Elzayady
Military Technical College
Computer Science & IT Electrical & Electronics Engineering

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A hybrid approach based on personality traits for hate speech detection in Arabic social media Hossam Elzayady; Mohamed S. Mohamed; Khaled M. Badran; Gouda I. Salama
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1979-1988

Abstract

In recent years, as social media has grown in popularity, people have gained the ability to freely share their views. However, this may lead to users' conflict and hostility, resulting in unattractive online environments. Hate speech relates to using expressions or phrases that are violent, offensive, or insulting to a minority of people. The number of Arab social media users is quickly rising, and this is being followed by an increase in the frequency of cyber hate speech in the area. Therefore, the automated detection of Arabic hate speech has become a major concern for many stakeholders. The intersection of personality learning and hate speech detection is a relatively less studied niche. We suggest a novel approach that is focused on extracting personality trait features and using these features to detect Arabic hate speech. The experimental results show that the proposed approach is superior in terms of the macro-F1 score by achieving 82.3% compared to previous work reported in the literature.
Co-Authors Gouda I. Salama Khaled M. Badran Mohamed S. Mohamed