Volume 3 Issue 1



Abstract : The need of social media has vividly changed people’s life with more and more sharing their thoughts,expressing opinions,and in the hunt for support on social media websites such as Twitter,Facebook,blogs e tc. Twitter,an online social networking and micro blogging service,which enables users to send and read text - based posts,known as tweets,with 140 - character limit. Newspapers and blogs express opinion of news entities (people,places,things) while expo sure to recent events. We present a system which extracts the sentiments from the online posts of twitter about news event. Our system shows sentiment identification,which expresses opinion associated with each entity. Also it consists of scoring phase,w hich assigns scores to each entity,on which the tweets are classified. Finally,we compare Maximum Entropy,Decision tree,Support vector machine and Naives Bayes classifiers.

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Downloads : 2002

Publication Date :

Modified Date : 2016-01-20

Cite/Export :

Varsha D. Jadhav , S.N. Deshmukh , "COMPARISON OF CLASSIFIERS FOR SENTIMENT ANALYSIS", IJIERT - International Journal of Innovations in Engineering Research and Technology, Volume 3 Issue 1, ISSN : 2394-3696, Page No.