Unigram Polarity Estimation of Movie Reviews using Maximum Likelihood

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Unigram Polarity Estimation of Movie Reviews using Maximum Likelihood

Author & Affiliation:

ROUNAK DHANERIYA ([email protected])

Department of Computer Science & Engineering, RGPV, Bhopal, (India)

MAHESH MOTWANI

Associate Professor, Department of Computer Science & Engineering, RGPV, Bhopal, (India)

MANISH AHIRWAR

Assitant Professor, Department of Computer Science & Engineering, RGPV, Bhopal, (India)

Keyword:

Sentiment Analysis, Polarity Detection, Intensity Estimation, Maximum Likelihood

Issue Date:

October, 2017

Abstract:

This research work focuses on sentiment analysis the detection of polarity and estimating the intensity of polarity of movie reviews. Internet movie database (IMDB) is the source of data named polarity dataset version 2.0 which is used in this research. There are 1000 reviews of movies for each category positive and negative. Unigram based Maximum likelihood algorithm is used which uses logarithmic likelihood ratios for estimating intensity and detection of polarity. This supervised technique is able to deal with complex sentences and detecting polarity of words. This approach uses unigram models to detect polarity and uses likelihood ratios for calculating the intensity. The results suggest that the sentiment analysis using unigram based maximum likelihood logic performs well.

Pages:

19-24

ISSN:

.-- (Online) - -- (Print)

Source:

Vol.1 - No.1

PDF:

Click here to download full paper

DOI:

http://dx.doi.org/

Copy the following to cite this article:

R. Dhaneriya; M. Motwani; M. Ahirwar , "Unigram Polarity Estimation of Movie Reviews using Maximum Likelihood", Ansari Journal of Ultra Scientist of Engineering and Management, Volume 1, Issue 1, Page Number 19-24, 2017

Copy the following to cite this URL:

Available from: http://www.enggandmgtjournal.org/paper/7/unigram-polarity-estimation-of-movie-reviews-using-maximum-likelihood