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Review Article

JCR. 2019; 6(6): 449-454


SURVEY OF VARIOUS ALGORITHMS USED IN TWITTER FOR SENTIMENT ANALYSIS

Jayakumar Sadhasivam, Ramesh Babu Kalivaradhan, Senthil Jayavel.

Abstract
Sentiment analysis is a process of finding polarity of the sentence and classify the sentence or document as positive and negative. There is a vast amount of data generated in social media in the form of blogs, comments, product reviews, tweets, status, etc. Sentiment analysis in Twitter has become a good research topic in recent years. As Twitter allows only 140 characters, it is very challenging to determine whether the tweet was a positive or negative tweet. There are many algorithms to analyse the polarity of the sentence. After studying major sentiment analysis algorithms, we evaluate the performance of these algorithms.

Key words: Sentiment Analysis, Nave Bayes, Support Vector Machine, Maximum Entropy Classifier, Ensemble Classifier.


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