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A Survey on Opinion Mining: From Stance to Product Aspect

Authors :
Jiasheng Si
Rui Wang
Yang Yang
Deyu Zhou
Mingmin Jiang
Source :
IEEE Access, Vol 7, Pp 41101-41124 (2019)
Publication Year :
2019
Publisher :
IEEE, 2019.

Abstract

With the prevalence of social media and online forum, opinion mining, aiming at analyzing and discovering the latent opinion in user-generated reviews on the Internet, has become a hot research topic. This survey focuses on two important subtasks in this field, stance detection and product aspect mining, both of which can be formalized as the problem of the triple (target, aspect, opinion) extraction. In this paper, we first introduce the general framework of opinion mining and describe the evaluation metrics. Then, the methodologies for stance detection on different sources, such as online forum and social media are discussed. After that, approaches for product aspect mining are categorized into three main groups which are corpus level aspect extraction, corpus level aspect, and opinion mining, and document level aspect and opinion mining based on the processing units and tasks. And then we discuss the challenges and possible solutions. Finally, we summarize the evolving trend of the reviewed methodologies and conclude the survey.

Details

Language :
English
ISSN :
21693536
Volume :
7
Database :
OpenAIRE
Journal :
IEEE Access
Accession number :
edsair.doi.dedup.....c983b0e4d1a198f37c4135b8984f3604