Sentiment Classification for Microblog by Machine Learning

With the development of microblog, many studies pay special attention to sentiment classification of the reviews in microblog. This paper summarizes three well-known methods for text classification and then improves one of them for sentiment analysis. We come up with a new model in which we introduc...

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Bibliographic Details
Published in2012 Fourth International Conference on Computational and Information Sciences pp. 286 - 289
Main Authors Zhen Niu, Zelong Yin, Xiangyu Kong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2012
Subjects
Bayesian methods
Feature extraction
Machine learning
microblog
Naïve Bayesian classifier
sentiment analysis
support vector machine
Support vector machines
Text categorization
text classification
Training
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Summary:With the development of microblog, many studies pay special attention to sentiment classification of the reviews in microblog. This paper summarizes three well-known methods for text classification and then improves one of them for sentiment analysis. We come up with a new model in which we introduce efficient approaches to select features, calculate weights, train samples and evaluate classifier. The new model is based on Bayesian algorithm and machine learning that is one of the most popular methods for sentiment classification. Our model can enhance the overall efficiency of the sentiment classifier.
ISBN:9781467324069
146732406X
DOI:10.1109/ICCIS.2012.276