Open Access   Article

PREDICTING SENTIMENT FROM MOVIE REVIEWS USING LEXICON BASED MODEL

Binita Verma1 , Ramjeevan Singh Thakur2 , Shailesh Jaloree3

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-10 , Page no. 28-34, Oct-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i10.2834

Online published on Oct 31, 2018

Copyright © Binita Verma, Ramjeevan Singh Thakur, Shailesh Jaloree . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Citation

IEEE Style Citation: Binita Verma, Ramjeevan Singh Thakur, Shailesh Jaloree, “PREDICTING SENTIMENT FROM MOVIE REVIEWS USING LEXICON BASED MODEL”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.28-34, 2018.

MLA Style Citation: Binita Verma, Ramjeevan Singh Thakur, Shailesh Jaloree "PREDICTING SENTIMENT FROM MOVIE REVIEWS USING LEXICON BASED MODEL." International Journal of Computer Sciences and Engineering 6.10 (2018): 28-34.

APA Style Citation: Binita Verma, Ramjeevan Singh Thakur, Shailesh Jaloree, (2018). PREDICTING SENTIMENT FROM MOVIE REVIEWS USING LEXICON BASED MODEL. International Journal of Computer Sciences and Engineering, 6(10), 28-34.

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Abstract

Large number of users shares their opinion on social networking sites. So, on the web an enormous quantity of data is generated daily. Usually there is not enough human resource to examine this data. The methods for automatic opinion mining on online data are becoming increasingly. From the past few years, methods have been developed that can successfully analyze the sentiment from digital text. These developments enable research into prediction of sentiment. Sentiment prediction has been used as a tool for movie review prediction. The aim of this work is to explore the use of lexicons to extract the sentiment prediction for a number of movie reviews. In this paper, a comparative analysis of lexicon based models has to predict the sentiments of movie reviews dataset together with evaluation metrics.

Key-Words / Index Term

Movie reviews, Lexicon based model, Predicting sentiment

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