 A systematic review on opinion mining and sentiment analysis in social mediaZaher Salah, Abdel-Rahman F. Al-Ghuwairi, Aladdin Baarah, Ahmad Aloqaily, Bar'a Qadoumi, Momen Alhayek and Bushra Alhijawi International Journal of Business Information Systems, 2019, vol. 31, issue 4, 530-554 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. Keywords: social network analysis; opinion mining; OM; sentiment analysis; SA; data mining techniques; information retrieval. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbisy:v:31:y:2019:i:4:p:530-554 Access Statistics for this article More articles in International Journal of Business Information Systems from Inderscience Enterprises Ltd |
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