Title: Text-based sentiment analysis: review

Authors: V.P. Lijo; Hari Seetha

Addresses: School of Computer Science and Engineering, VIT University, Vellore-632014, Tamil Nadu, India ' School of Computer Science and Engineering, VIT University, Vellore-632014, Tamil Nadu, India

Abstract: The impact of the social networks-based sentiment analysis (SA) and opinion mining has increased in recent times. Decision-makers consider the opinions of the thought leaders and laymen, and plenty of opinions are available in social networks. When a user wants to get a service or buy a product he or she will check for the reviews and opinions provided by other people about various offerings. Opinion rich data sources are available in digital form; this attracts many researchers to focus research on SA. The 'sentiments' available in social networks and review pages are highly valuable for industries and individuals who want to closely monitor their reputation and live feedback about their services and products. This paper presents a review covering techniques, tools, data resources and applications in the area of text-based SA.

Keywords: sentiment analysis; SA; feature selection; text mining; semantic orientation; SO; text classification; opinion mining; lexicon.

DOI: 10.1504/IJKL.2017.088163

International Journal of Knowledge and Learning, 2017 Vol.12 No.1, pp.1 - 26

Received: 08 Feb 2016
Accepted: 06 Nov 2016
Published online: 27 Nov 2017 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article