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A Systematic Review for Sentiment Analysis of Arabic Dialect Texts Researches

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Proceedings of International Conference on Emerging Technologies and Intelligent Systems (ICETIS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 322))

Abstract

People in the Arab world prefer to use their dialects in writing while using social media sites which results in generating a significant amount of texts. Sentiment analysis in texts is one of the most important applications of the Natural Language Processing field of science. Sentiment Analysis involves classifying texts based upon emotions or polarity. Different approaches have been utilized so far for Sentiment Analysis of Arabic Texts. In this systematic review, the author aims to explore the researches and studies that were in the field of Sentiment Analysis of Arabic Dialects to report the utilized approaches, constructed datasets, most common type of dialects explored by researchers, and reported results of Sentiment Analysis in term of accuracy, recall, precision, and F-Measure. Author reported the following findings for this systematic review: (1) in most of the included research papers the dialect type is not specified and mostly it was mentioned (Arabic Dialects) in general, however, some other dialects were explored specifically by authors such as Saudi Dialect (2) 50% of the utilized datasets in the included research papers are constructed by the authors themselves, moreover, the size of most of the utilized datasets are between 10,000 and 50,000, and very limit number of datasets had size above 100,000, (3) machine learning algorithms (classifiers) are the most common approach that were used for Sentiment Analysis of Arabic Dialects (4) the best result for Sentiment Analysis of Arabic Dialects achieved while different machine learning algorithms (classifiers) were used, and (5) among social media platforms, Twitter is the most common utilized online platform for constructing datasets for Arabic Dialects texts.

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Acknowledgements

This work is a part of a project submitted to The British University in Dubai.

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Authors and Affiliations

  1. Faculty of Engineering and IT, The British University in Dubai, 345015, Dubai, United Arab Emirates

    Arwa A. Al Shamsi & Sherief Abdallah

Authors
  1. Arwa A. Al Shamsi
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  2. Sherief Abdallah
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Corresponding author

Correspondence to Arwa A. Al Shamsi .

Editor information

Editors and Affiliations

  1. The British University in Dubai, Dubai, United Arab Emirates

    Mostafa Al-Emran

  2. Universiti Teknologi Malaysia, Johor, Malaysia

    Mohammed A. Al-Sharafi

  3. Al Buraimi University College, Al Buraimi, Oman

    Mohammed N. Al-Kabi

  4. The British University in Dubai, Dubai, United Arab Emirates

    Khaled Shaalan

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Al Shamsi, A.A., Abdallah, S. (2022). A Systematic Review for Sentiment Analysis of Arabic Dialect Texts Researches. In: Al-Emran, M., Al-Sharafi, M.A., Al-Kabi, M.N., Shaalan, K. (eds) Proceedings of International Conference on Emerging Technologies and Intelligent Systems. ICETIS 2021. Lecture Notes in Networks and Systems, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-030-85990-9_25

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