• Prakash Ra
• Repana Reddy Sekhar b

Social networking sites frequently use brief text messages to convey a range of emotions. We can identify the different emotions that the crowd is expressing such as joy, sorrow, fear, worry, etc., by examining brief sentences. We can ascertain a reviewer's general sentiment or opinion on a movie by using IMDb sentiment analysis. The Problem presents a contemporary method for utilizing the Navies-Bayes classifier for sentiment analysis of movie reviews. The implementation of machine learning and prediction algorithms is made possible by the examination of a document as a set of numbers. Therefore, we could easily create avenues for machine learning algorithms to be used if there were a means to translate these words intended for human perception and interpretation into numbers.

Support vectors, Classification, Short texts, Microblog, Naïve-Bayes.

" Sentiment Analysis on IMDb Movie Reviews using Navies-Bayes Classifier for the Problem of Classifying the Polarity of the Text", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.7-19, May-2019, Available :http://www.jetir.org/papers/JETIR1905Z02.pdf

" Sentiment Analysis on IMDb Movie Reviews using Navies-Bayes Classifier for the Problem of Classifying the Polarity of the Text", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp7-19, May-2019, Available at : http://www.jetir.org/papers/JETIR1905Z02.pdf