Mining Movie Reviews using Machine Learning Techniques

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
N. Sudha, M. Govindarajan
10.5120/ijca2016910284

N Sudha and M Govindarajan. Mining Movie Reviews using Machine Learning Techniques. International Journal of Computer Applications 144(5):34-36, June 2016. BibTeX

@article{10.5120/ijca2016910284,
	author = {N. Sudha and M. Govindarajan},
	title = {Mining Movie Reviews using Machine Learning Techniques},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2016},
	volume = {144},
	number = {5},
	month = {Jun},
	year = {2016},
	issn = {0975-8887},
	pages = {34-36},
	numpages = {3},
	url = {http://www.ijcaonline.org/archives/volume144/number5/25178-2016910284},
	doi = {10.5120/ijca2016910284},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Sentiment analysis has been observed as an important subject in data mining because of the wide range of direct applications such as analysis of products, customer profiles, and political trends and so on. It is the process of identifying people’s attitude and emotional state from language to language. In Natural Language Processing, sentiment analysis is an automated task where machine learning is used to rapidly determine the sentiment of large amounts of text or speech.In this research work a comparative study of effectiveness in which some of the Machine learning techniques like naïve bayes and support vector machine. The results observed and noted that naïve bayes performs better in terms of accuracy, precision, recall and F-Measure for movie review.

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Keywords

Sentiment analysis, opinion extraction, reviews, Support vector machine, Naïve bayes