Feature Selection for Sentiment Analysis by using SVM

Rohini S. Rahate; Emmanuel M

Research Article

Feature Selection for Sentiment Analysis by using SVM

by Rohini S. Rahate, Emmanuel M

International Journal of Computer Applications

Foundation of Computer Science (FCS), NY, USA

Volume 84 - Issue 5

Published: December 2013

Authors: Rohini S. Rahate, Emmanuel M

10.5120/14573-2697

PDF

Rohini S. Rahate, Emmanuel M . Feature Selection for Sentiment Analysis by using SVM. International Journal of Computer Applications. 84, 5 (December 2013), 24-32. DOI=10.5120/14573-2697

                        @article{ 10.5120/14573-2697,
                        author  = { Rohini S. Rahate,Emmanuel M },
                        title   = { Feature Selection for Sentiment Analysis by using SVM },
                        journal = { International Journal of Computer Applications },
                        year    = { 2013 },
                        volume  = { 84 },
                        number  = { 5 },
                        pages   = { 24-32 },
                        doi     = { 10.5120/14573-2697 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }

                        %0 Journal Article
                        %D 2013
                        %A Rohini S. Rahate
                        %A Emmanuel M
                        %T Feature Selection for Sentiment Analysis by using SVM%T 
                        %J International Journal of Computer Applications
                        %V 84
                        %N 5
                        %P 24-32
                        %R 10.5120/14573-2697
                        %I Foundation of Computer Science (FCS), NY, USA

Abstract

Sentiment analysis depends on feature selection methods to approaches that use general statistical measures where features are selected on empirical evidence. Empirical evidence (research) is a way of gaining knowledge by means of direct and indirect observation or experience. there are new features selection schemes that use a content and syntax model that is used to automatically learn a set of features in a review document and removing the entities that are being reviewed from the subjective expression that describe those entities in terms of polarities.

References

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Index Terms

Computer Science

Information Sciences

No index terms available.

Keywords

Sentiment analysis feature selection syntax model sentiment levels movie domain