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Advanced Computational Methods for Knowledge EngineeringTwitter Sentiment Analysis Using Machine Learning Techniques

Advanced Computational Methods for Knowledge Engineering: Twitter Sentiment Analysis Using... [Twitter is a microblogging site in which users can post updates (tweets) to friends (followers). It has become an immense dataset of the so-called sentiments. In this paper, we introduce an approach to selection of a new feature set based on Information Gain, Bigram, Object-oriented extraction methods in sentiment analysis on social networking side. In addition, we also proposes a sentiment analysis model based on Naive Bayes and Support Vector Machine. Its purpose is to analyze sentiment more effectively. This model proved to be highly effective and accurate on the analysis of feelings.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Advanced Computational Methods for Knowledge EngineeringTwitter Sentiment Analysis Using Machine Learning Techniques

Part of the Advances in Intelligent Systems and Computing Book Series (volume 358)
Editors: Le Thi, Hoai An; Nguyen, Ngoc Thanh; Do, Tien Van

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References (10)

Publisher
Springer International Publishing
Copyright
© Springer International Publishing Switzerland 2015
ISBN
978-3-319-17995-7
Pages
279–289
DOI
10.1007/978-3-319-17996-4_25
Publisher site
See Chapter on Publisher Site

Abstract

[Twitter is a microblogging site in which users can post updates (tweets) to friends (followers). It has become an immense dataset of the so-called sentiments. In this paper, we introduce an approach to selection of a new feature set based on Information Gain, Bigram, Object-oriented extraction methods in sentiment analysis on social networking side. In addition, we also proposes a sentiment analysis model based on Naive Bayes and Support Vector Machine. Its purpose is to analyze sentiment more effectively. This model proved to be highly effective and accurate on the analysis of feelings.]

Published: Jan 1, 2015

Keywords: Twitter; sentiment analysis; sentiment classification

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