Unigram Polarity Estimation of Movie Reviews using Maximum Likelihood
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.
Keywords: Sentiment Analysis, Polarity Detection, Intensity Estimation, Maximum Likelihood
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ABOUT THE AUTHORS
Rounak Dhaneriya
Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India
Manish Ahirwar
Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India
Mahesh Motwani
Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India
Rounak Dhaneriya
Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India
Manish Ahirwar
Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India
Mahesh Motwani
Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India