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Design of Sentiment Analysis System using Polarity Classification Technique

by Rajeshwar Rao Kodipaka, Sanjeeva Polepaka, Md. Rafeeq
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 125 - Number 15
Year of Publication: 2015
Authors: Rajeshwar Rao Kodipaka, Sanjeeva Polepaka, Md. Rafeeq
10.5120/ijca2015906159

Rajeshwar Rao Kodipaka, Sanjeeva Polepaka, Md. Rafeeq . Design of Sentiment Analysis System using Polarity Classification Technique. International Journal of Computer Applications. 125, 15 ( September 2015), 22-24. DOI=10.5120/ijca2015906159

@article{ 10.5120/ijca2015906159,
author = { Rajeshwar Rao Kodipaka, Sanjeeva Polepaka, Md. Rafeeq },
title = { Design of Sentiment Analysis System using Polarity Classification Technique },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 125 },
number = { 15 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 22-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume125/number15/22509-2015906159/ },
doi = { 10.5120/ijca2015906159 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:16:07.911406+05:30
%A Rajeshwar Rao Kodipaka
%A Sanjeeva Polepaka
%A Md. Rafeeq
%T Design of Sentiment Analysis System using Polarity Classification Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 125
%N 15
%P 22-24
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Twitter is a medium that we can use for communication. All posted tweets we can store in one location and create archive. Archive contains new and old tweets. Now we can start the analyzation on archive tweets that’s we can design effective sentiment analysis system. This paper main aim is to determine parts of speech opinion words using polarity classification technique and support vector machine learning algorithm. Surveys of methods are used in various levels of sentiment analysis. It does analyze the tweets information in limited levels of content only. Now in this paper we design new sentiment analysis tool using polarity classification technique. Polarity classification techniques discover top 20-emoticons, learning different classes of words and other features information. These techniques perform in depth tweets analysis. It does provide better analysis results compare to previous methods.

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Index Terms

Computer Science
Information Sciences

Keywords

Sentiment analysis opinion mining text documents support vector machine classifier polarity classification technique.

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