Sentiment Analysis of Chinese Micro Blog Using Machine Learning and an Improved Feature Selection Method

Abstract:

With the rapid development of Internet and occurrence of social media services, many users are becoming the creators of social information. However, the normal manual work can't deal with a large number of subjective messages. As a new kind of social media service, micro blog has been widely accepted and can be used for sentiment analysis. This paper compared performances of three machine learning methods on sentiment analysis of Chinese micro blog. We also proposed an improved feature selection method that increases the accuracy of classification. Experiment results show that SVM is closed to Naïve Bayes and they are better than logistic regression in most cases.

• Periodical: Applied Mechanics and Materials (Volumes 631-632)
• Pages: 1219-1223
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.631-632.1219
• Online since: September 2014
• Authors: Jia Hao Chen*, Jian Hua Wu
• Keywords: Feature Selection, Machine Learning, Micro Blog, Sentiment Analysis

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