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All Journal International Journal of Electrical and Computer Engineering
Khaled Alrifai
Higher Institute for Applied Sciences and Technology
Computer Science & IT Electrical & Electronics Engineering

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Arabic tweeps dialect prediction based on machine learning approach Khaled Alrifai; Ghaida Rebdawi; Nada Ghneim
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1627-1633

Abstract

In this paper, we present our approach for profiling Arabic authors on twitter, based on their tweets. We consider here the dialect of an Arabic author as an important trait to be predicted. For this purpose, many indicators, feature vectors and machine learning-based classifiers were implemented. The results of these classifiers were compared to find out the best dialect prediction model. The best dialect prediction model was obtained using random forest classifier with full forms and their stems as feature vector.
Co-Authors Ghaida Rebdawi Nada Ghneim