Text Mining Techniques for Sentiment Analysis of Arabic Dialects: Literature Review

A. Al Shamsi, Arwa; Abdallah, Sherief

Text Mining Techniques for Sentiment Analysis of Arabic Dialects: Literature Review

Date

2021

Authors

A. Al Shamsi, Arwa

Abdallah, Sherief

Publisher

ASTESJ

Abstract

Social media attracts a lot of users around the world. Many reasons drive people to use social media sites such as expressing opinions and ideas, displaying their diaries and sharing them with others, social communication with family and friends and building new social relationships, learning and sharing knowledge. Written text is one of the most common forms used for communication while using social media sites. People use written texts in different languages, and due to the increased usage of social networking sites around the world, the amount of texts and data resulting from this use is large. These generated data considered as a valuable source of information that attracted business owners, companies, government institutions, and of course, it attracts researchers and data scientists as well. Researchers and data scientists increasingly presented great efforts in investigating and analyzing Arabic Language texts. Most of these efforts targeted the Modern Standard form of Arabic Language. While exploring the social media sites, most of the Arab users tend to use their dialects while utilizing Social Media sites, which results in generating a massive amount of Arabic Dialects texts. The number of researches and analysis of Dialects' form of the Arabic language are limited, however, it is increasing recently. This literature review aims to explore approaches and methods used for Sentiment Analysis of Arabic Dialects text.

Keywords

Natural Language Processing Arabid Dialects Sentiment Analysis

Citation

Shamsi, A.A.A. and Abdallah, S. (2021) “Text Mining Techniques for Sentiment Analysis of Arabic Dialects: Literature Review,” Advances in Science, Technology and Engineering Systems Journal, 6(1), pp. 1012–1023.