Abstract
The popularity of World Wide Web has brought a latest way of expressing the sentiments of individuals. Millions of users express their sentiments on Twitter, making it a precious platform for analyzing the public sentiment. This paper proposes a 3-step algorithm for sentiment analysis. Cleaning, Entity identification, and Classification are the 3 steps. Finally we measure the performance of the classifier using recall, precision and accuracy.
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Supriya, B.N., Kallimani, V., Prakash, S., Akki, C.B. (2016). Twitter Sentiment Analysis Using Binary Classification Technique. In: Vinh, P., Barolli, L. (eds) Nature of Computation and Communication. ICTCC 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 168. Springer, Cham. https://doi.org/10.1007/978-3-319-46909-6_36
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DOI: https://doi.org/10.1007/978-3-319-46909-6_36
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