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Sentiment Analysis of Movie Reviews using POS tags and Term Frequencies

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 96 - Number 25
Year of Publication: 2014
Authors:
Oaindrila Das
Rakesh Chandra Balabantaray
10.5120/16952-7048

Oaindrila Das and Rakesh Chandra Balabantaray. Article: Sentiment Analysis of Movie Reviews using POS tags and Term Frequencies. International Journal of Computer Applications 96(25):36-41, June 2014. Full text available. BibTeX

@article{key:article,
	author = {Oaindrila Das and Rakesh Chandra Balabantaray},
	title = {Article: Sentiment Analysis of Movie Reviews using POS tags and Term Frequencies},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {96},
	number = {25},
	pages = {36-41},
	month = {June},
	note = {Full text available}
}

Abstract

Sentiment analysis and opinion mining play an important role in judging and predicting people's views. Recently, sentiment analysis has focused on assigning positive and negative polarities to opinions. More methods are being devised to find the weightage of a particular expression in a sentence, whether the particular expression gives the sentence a positive, negative or a neutral meaning. Most of the work on sentiment analysis in the past has been carried out by determining the strength of a subjective expression within a sentence using the parts of speech. Sentiment analysis tries to classify opinion sentences in a document on the basis of their polarity as positive or negative, which can be used in various ways and in many applications for example, marketing and contextual advertising, suggestion systems based on the user likes and ratings, recommendation systems etc. This paper presents a novel approach for classification of online movie reviews using parts of speech and machine learning algorithms.

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