文章基本信息

标题：Unigram Polarity Estimation of Movie Reviews using Maximum Likelihood
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作者：Rounak Dhaneriya ; Manish Ahirwar ; Mahesh Motwani 等
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2016
卷号：13
期号：5
出版社：IJCSI Press
摘要：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.
关键词：Sentiment Analysis; Polarity Detection; Intensity Estimation; Maximum Likelihood