International Journal of Science , Engineering and Management (IJSEM)

Monthly Journal for Science , Engineering and Management

Volume3,April 2018,

Topic : Opinion Mining On Twitter Data for Sentiment Classification

Authors:G. Anuradha || CH. Raga Madhuri, M.Srikanth

Abstract:Opinion mining and Sentiment analysis gives sentiments, opinions and subjectivity of text. Now a days many people express their opinions and ideas through social networking sites like Face book, Google+ and Twitter. These are platforms to allow people to share and express their views about topics, have discussion with different communities. Twitter data is short and continues data suitable for sentiment analysis. This paper focus on sentiment classification (positive, negative and neutral) which is multistep process involves preprocessing phase, parts of tagging (POT), and calculating polarity and apply three classification algorithms that are Decision tree, Naïve bayes and Support vector machine on twitter data in Jupiter. This paper also presents empirical comparison of classification algorithms in which decision tree algorithm is highest accuracy in comparison of all three algorithms considered in this study..

Keywords: Naïve-Bayes, Decision Tree, Support Vector Machine, POT, Polarity.

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DOI: 01.1617/vol5/iss4/pid17036


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Editor-in-Chief

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Dr.Muhammad Ishtiaq,
Mirpur University of
Science & Technology,
Mirpur, Azad Kasmir.

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IMPACT FACTOR: 2.7

ISSN(Online): 2456-1304

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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ACCEPTANCE RATIO: 25%
ARTICLES PUBLISHED:00007
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Journal Code : IJSEM
Electronic ISSN : 2456-1304
Impact Factor : 2.7
Frequency : Monthly
Contact : editor@ijsem.org

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