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Sentiment Analysis of Arabic Sequential Data Using Traditional and Deep Learning: A Review

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The Fourth Industrial Revolution: Implementation of Artificial Intelligence for Growing Business Success

Part of the book series: Studies in Computational Intelligence ((SCI,volume 935))

Abstract

With the emergence of social media and review sites peoples express their opinions toward entities, generating a huge amount of data or what is called big data that comes in non structured form of sequential data such as tweets or reviews. The availability of big data leads to the excitement in Artificial Intelligence and many applications such as Sentiment Analysis (SA). Although many studies conducted in SA, however majority of them focused on English, while that consider the Arabic one are very limited due to many challenges like variation of dialects, morphological attributes, and the lack of Arabic sources and corpora, despite the spread of the Arabic language and its frequent use in social media. The objective of this review is to highlight different studies of Arabic sequential data that utilized traditional and deep learning techniques.

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Author information

Authors and Affiliations

  1. College of Engineering, Design and Physical Sciences, Department of Computer Science, Brunel University London, London, UK

    Thuraya. M. Omran & Crina Grosan

  2. College of Information Technology, Department of Information Technology, Ahlia University, Manama, Kingdom of Bahrain

    Baraa T. Sharef

Authors
  1. Thuraya. M. Omran
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  2. Baraa T. Sharef
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  3. Crina Grosan
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Corresponding author

Correspondence to Baraa T. Sharef .

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Editors and Affiliations

  1. College of Business and Finance, Ahlia University, Manama, Bahrain

    Allam Hamdan

  2. Information Technology Department, Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  3. College of Business and Finance, Ahlia University, Manama, Bahrain

    Anjum Razzaque

  4. Middle East Technical University - Northern Cyprus Campus, Kalkanlı, Güzelyurt, KKTC, Turkey

    Bahaaeddin Alareeni

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Omran, T.M., Sharef, B.T., Grosan, C. (2021). Sentiment Analysis of Arabic Sequential Data Using Traditional and Deep Learning: A Review. In: Hamdan, A., Hassanien, A.E., Razzaque, A., Alareeni, B. (eds) The Fourth Industrial Revolution: Implementation of Artificial Intelligence for Growing Business Success. Studies in Computational Intelligence, vol 935. Springer, Cham. https://doi.org/10.1007/978-3-030-62796-6_26

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