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Opinion Mining: A Survey

by K.g. Nandha Kumar, T Christopher
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 113 - Number 2
Year of Publication: 2015
Authors: K.g. Nandha Kumar, T Christopher
10.5120/19797-1576

K.g. Nandha Kumar, T Christopher . Opinion Mining: A Survey. International Journal of Computer Applications. 113, 2 ( March 2015), 15-17. DOI=10.5120/19797-1576

@article{ 10.5120/19797-1576,
author = { K.g. Nandha Kumar, T Christopher },
title = { Opinion Mining: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 113 },
number = { 2 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 15-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume113/number2/19797-1576/ },
doi = { 10.5120/19797-1576 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:49:54.382105+05:30
%A K.g. Nandha Kumar
%A T Christopher
%T Opinion Mining: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 113
%N 2
%P 15-17
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Opining mining has gained high level focus in business and commercial fields. The opinions are considered as valuable data. Opinions are customer reviews, comments and feelings and collected from web forums, websites, and user groups which are posted by thousands of end users and also recorded manually. The collected opinions are processed by various techniques, algorithms, methods and software tools in order to extract the meaning from them. Extraction of meaningful information from opinions is given more importance in the field of business analytics. This entire process is popularly known as opinion mining or sentiment analysis and they are used in industries to develop quality of services, products. This article is an outcome of a study which made on various sub tasks, approaches, methods and techniques involved and applied in opinion mining.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Opinion Sentiment Classification Machine Learning NLP.

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