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Sentiment Analysis Application in E-Commerce: Current Models and Future Directions

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Electronic Government and the Information Systems Perspective (EGOVIS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14149))

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Abstract

Sentiment analysis (SA), which is also known as opinion mining, is an increasingly popular practical application of Natural Language Processing (NLP). SA is especially useful in e-commerce fields, where comments and reviews often contain a wealth of valuable business information that has great research value. This study aims to investigate three related aspects of SA in e-commerce: the methods used to address the SA problem in this domain, the most commonly used e-commerce platforms where researchers get data from, and the future direction of research in this area. To achieve this goal, we reviewed 15 papers that covered many machine learning models and deep learning models. In the results and discussion section, we suggest several future directions that can improve the current SA models in this review. By addressing the limitations of existing SA models and exploring new approaches, we believe that future research in this area will lead to more accurate and effective sentiment analysis tools that can benefit both businesses and consumers.

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Authors and Affiliations

  1. Malaya University, Kuala Lumpur, Malaysia

    Huang Huang, Adeleh Asemi & Mumtaz Begum Mustafa

Authors
  1. Huang Huang
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  2. Adeleh Asemi
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  3. Mumtaz Begum Mustafa
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Corresponding author

Correspondence to Huang Huang .

Editor information

Editors and Affiliations

  1. Corvinus University of Budapest, Budapest, Hungary

    Andrea Kö

  2. Italian National Research Council, Florence, Italy

    Enrico Francesconi

  3. University of Malaya, Kuala Lumpur, Malaysia

    Adeleh Asemi

  4. Johannes Kepler University Linz, Linz, Austria

    Gabriele Kotsis

  5. Vienna University of Technology, Vienna, Austria

    A Min Tjoa

  6. Johannes Kepler University Linz, Linz, Austria

    Ismail Khalil

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Huang, H., Asemi, A., Mustafa, M.B. (2023). Sentiment Analysis Application in E-Commerce: Current Models and Future Directions. In: Kö, A., Francesconi, E., Asemi, A., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Electronic Government and the Information Systems Perspective. EGOVIS 2023. Lecture Notes in Computer Science, vol 14149. Springer, Cham. https://doi.org/10.1007/978-3-031-39841-4_5

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  • DOI: https://doi.org/10.1007/978-3-031-39841-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-39840-7

  • Online ISBN: 978-3-031-39841-4

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