Sentiment Analysis Using Twitter Data

International Journal of Computer Trends and Technology (IJCTT)          
© 2019 by IJCTT Journal
Volume-67 Issue-5
Year of Publication : 2019
Authors : Remya B Nair, Sruthimol E K
DOI :  10.14445/22312803/IJCTT-V67I5P114


MLA Style:Remya B Nair, Sruthimol E K"Sentiment Analysis Using Twitter Data" International Journal of Computer Trends and Technology 67.5 (2019): 82-84.

APA Style:Remya B Nair, Sruthimol E K (2019). Sentiment Analysis Using Twitter Data International Journal of Computer Trends and Technology, 67(5), 82-84.

Sentiment analysis is the process of computationally identifying and categorizing opinions expressed in a piece of text. Sentiment analysis is also known as opinion mining. It is a field with natural language processing that builds system that try to identify and express opinions within the text. In this paper we are using twitter data for analysing sentiments. Tweets are collected from twitter using twitter API, analyses and classifies these tweets. Naive Bayes classifier is used for classifying tweets in order to obtain the result as positive, negative or neutral.

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Sentiment analysis, naïve Bayes, polarity, tokens, unigram, chi-square