Machine Learning Methods in Classification of Text by Sentiment Analysis of Social Networks

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I. Hemalatha
Dr. G.P.Saradhi Varma, Dr. A.Govardhan


In recent years, we became witnesses of a large number of websites that enable users to contribute, modify, and grade the content. Users have an opportunity to express their personal opinion about specific topics. The examples of such web sites include blogs, forums, product review sites, and social networks. Micro-blogs are a challenging new source of information for data mining techniques. It allows users to publish brief message updates, which can be submitted in many different channels, including the Web and text messaging service. One of the most notable micro-blogging services is Twitter, Face Book Etc.,. Twitter messages are short, and generated constantly, and well suited for knowledge discovery. This paper presents an empirical study of efficiency of machine learning techniques in classifying text messages by sentiment Analysis.



Keywords: Blogs, Machine Learning, Sentiment Analysis.


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