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Aspect-based Opinion Mining: A Survey

by K. Vivekanandan, J. Soonu Aravindan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 106 - Number 3
Year of Publication: 2014
Authors: K. Vivekanandan, J. Soonu Aravindan
10.5120/18501-9566

K. Vivekanandan, J. Soonu Aravindan . Aspect-based Opinion Mining: A Survey. International Journal of Computer Applications. 106, 3 ( November 2014), 21-26. DOI=10.5120/18501-9566

@article{ 10.5120/18501-9566,
author = { K. Vivekanandan, J. Soonu Aravindan },
title = { Aspect-based Opinion Mining: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 106 },
number = { 3 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 21-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume106/number3/18501-9566/ },
doi = { 10.5120/18501-9566 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:38:25.655954+05:30
%A K. Vivekanandan
%A J. Soonu Aravindan
%T Aspect-based Opinion Mining: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 106
%N 3
%P 21-26
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Opinion mining has been an emerging research field in Computational Linguistics, Text Analysis and Natural Language Processing (NLP) in recent years. It is the computational study of people's opinions towards entities and their aspects. Entities usually refer to individuals, events, topics, products and organizations. Aspects are attributes or components of entities. In the last few years, social media has become an excellent source to express and share people's opinion on entities and their aspects. With the availability of vast opinionated web contents in the form of comments, reviews, blogs, tweets, status updates, etc. it is harder for people to analyze all opinions at a time to make good decisions. So, there is a need for effective automated systems to evaluate opinions and generate accurate results. Sentiment Analysis, Emotion Analysis, Subjectivity Detection has also become an active research area in recent years along with opinion mining. This article presents a brief overview of opinion mining and its classifications and specifically focuses on the sub topic aspect-based opinion mining, its approaches, metrics used for evaluation and latest research challenges.

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Index Terms

Computer Science
Information Sciences

Keywords

Sentiment Analysis Emotion Analysis Subjectivity Detection Polarity Detection Text Analysis.

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