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

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

Addresses: Prince Hussein Bin Abdullah II for Information Technology, Hashemite University, P.O. Box 150459, Zarqa 13115, Jordan ' Prince Hussein Bin Abdullah II for Information Technology, Hashemite University, P.O. Box 150459, Zarqa 13115, Jordan ' Prince Hussein Bin Abdullah II for Information Technology, Hashemite University, P.O. Box 150459, Zarqa 13115, Jordan ' Prince Hussein Bin Abdullah II for Information Technology, Hashemite University, P.O. Box 150459, Zarqa 13115, Jordan ' Prince Hussein Bin Abdullah II for Information Technology, Hashemite University, P.O. Box 150459, Zarqa 13115, Jordan ' Prince Hussein Bin Abdullah II for Information Technology, Hashemite University, P.O. Box 150459, Zarqa 13115, Jordan ' Prince Hussein Bin Abdullah II for Information Technology, Hashemite University, P.O. Box 150459, Zarqa 13115, Jordan

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.

DOI: 10.1504/IJBIS.2019.101585

International Journal of Business Information Systems, 2019 Vol.31 No.4, pp.530 - 554

Received: 01 Apr 2017
Accepted: 28 Oct 2017
Published online: 13 Aug 2019 *

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