Sentiment Analysis of movie reviews: A new feature-based sentiment classification

Ketan Sarvakar¹ , Urvashi K Kuchara²

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.3 , pp.8-12, Jun-2018

CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v6i3.812

Online published on Jun 30, 2018

Copyright © Ketan Sarvakar, Urvashi K Kuchara . 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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Abstract :
Sentiment Analysis also known as opinion mining is the task of detecting, extracting and classifying opinions or sentiments related to different topics. One such area of interest is sentiment classification or polarity determination of movie reviews in user specific choice which are dependent on either mood or emotion of user perspectives. This plays an important role in today’s world where the promotion of nay product or movies. Polarity determination is an important task for both the user and producer. They can take appropriate decision based on these results of classification. Thus, considering the needs and developing interests in social data mining and increasing dependency of users on customer reviews here we proposed a method to classify the data more accurately by altering the pre-processing tasks mainly filtering. Proposed methodology will be used for the available classification techniques by using the available dataset more consistently by working on the dictionary built by the filters.

Key-Words / Index Term :
Sentiment Analysis; Dictionary; tokenizer; Accuracy; StringToWordVector, CustomStringToWordVector filter

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