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Reseach Article

Literature Review on Feature Identification in Sentiment Analysis

by Altaf Hussain, Shafaq Sattar, Muhammad Tanvir Afzal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 132 - Number 3
Year of Publication: 2015
Authors: Altaf Hussain, Shafaq Sattar, Muhammad Tanvir Afzal

Altaf Hussain, Shafaq Sattar, Muhammad Tanvir Afzal . Literature Review on Feature Identification in Sentiment Analysis. International Journal of Computer Applications. 132, 3 ( December 2015), 22-27. DOI=10.5120/ijca2015907331

@article{ 10.5120/ijca2015907331,
author = { Altaf Hussain, Shafaq Sattar, Muhammad Tanvir Afzal },
title = { Literature Review on Feature Identification in Sentiment Analysis },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 132 },
number = { 3 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 22-27 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2015907331 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:28:09.812858+05:30
%A Altaf Hussain
%A Shafaq Sattar
%A Muhammad Tanvir Afzal
%T Literature Review on Feature Identification in Sentiment Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 132
%N 3
%P 22-27
%D 2015
%I Foundation of Computer Science (FCS), NY, USA

Now-a-days the volume of opinions about products, issues, events, and politics etc. on different social, e-commerce and review sites grows very rapidly. From both opinion holder and opinion target point of view, it is very difficult and time consuming task to analyze all the reviews from this massive amount of data on the web. So, there is a need of efficient method that automatically extracts the opinions and relevant features of the opinion target from the reviews and finally generates the feature wise summary. Sometimes people may use different words to express same feature, this may produce a misperception in the results during feature wise summary generation. To avoid this, we need to categorize similar features for precise classification of opinions based on these feature groups. Therefore, our study is targeting the most important tasks of feature based sentiment analysis that are feature extraction and feature categorization. This paper is about to cover the currently available techniques in these two areas. We have also focused on least addressed area in this domain giving an opportunity to researchers for future work.

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Index Terms

Computer Science
Information Sciences


Feature Grouping Feature Extraction Feature Identification Feature Clustering Sentiment Analysis