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A systematic review on opinion mining and sentiment analysis in social media

Author

Listed:
  • Zaher Salah
  • Abdel-Rahman F. Al-Ghuwairi
  • Aladdin Baarah
  • Ahmad Aloqaily
  • Bar'a Qadoumi
  • Momen Alhayek
  • Bushra Alhijawi

Abstract

This paper employed information retrieval and statistical techniques for producing systematic literature review (SLR). Sentiment analysis (SA) and opinion mining (OM) in social media domain were considered as a case study to produce an example of SLR. The produced SLR introduced the field of SA and OM and surveyed current issues in user content based mining in social media field. SLR retrieves and evaluates the multiple relevant research papers concerning specific research questions. The paper details different approaches for conducting SA and OM and provides a common framework for searching and selection procedure applied to extracting the research papers that cover comprehensively the intended research directions in the field. This systematic review investigates the SA and OM techniques that are found in more than 60 specialised research papers in the field of data mining with respect to social media.

Suggested Citation

  • Zaher Salah & Abdel-Rahman F. Al-Ghuwairi & Aladdin Baarah & Ahmad Aloqaily & Bar'a Qadoumi & Momen Alhayek & Bushra Alhijawi, 2019. "A systematic review on opinion mining and sentiment analysis in social media," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 31(4), pages 530-554.
    • Handle: RePEc:ids:ijbisy:v:31:y:2019:i:4:p:530-554
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    Cited by:

    1. Intan Nurma Yulita & Victor Wijaya & Rudi Rosadi & Indra Sarathan & Yusa Djuyandi & Anton Satria Prabuwono, 2023. "Analysis of Government Policy Sentiment Regarding Vacation during the COVID-19 Pandemic Using the Bidirectional Encoder Representation from Transformers (BERT)," Data, MDPI, vol. 8(3), pages 1-17, February.

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