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Twitter Users' Classification Based on Interest: Case Study on Arabic Tweets
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Author(s): Noura A. AlSomaikhi (King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia)and Zakarya A. Alzamil (King Saud University, Riyadh, Saudi Arabia)
Copyright: 2020
Volume: 10
Issue: 1
Pages: 12
Source title:
International Journal of Information Retrieval Research (IJIRR)
Editor(s)-in-Chief: Zhongyu Lu (University of Huddersfield, UK)
DOI: 10.4018/IJIRR.2020010101
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Abstract
Microblogging platforms, such as Twitter, have become a popular interaction media that are used widely for different daily purposes, such as communication and knowledge sharing. Understanding the behaviors and interests of these platforms' users become a challenge that can help in different areas such as recommendation and filtering. In this article, an approach is proposed for classifying Twitter users with respect to their interests based on their Arabic tweets. A Multinomial Naïve Bayes machine learning algorithm is used for such classification. The proposed approach has been developed as a web-based software system that is integrated with Twitter using Twitter API. An experimental study on Arabic tweets has been investigated on the proposed system as a case study.
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