The entertainment for the real-world peoples is very huge and analyzing such kind of entertainments are not easy. One of the areas of this topic is movies. Different types of movie reviews are produced by various reviewers. Some of the movies create a high impact in the society as well as it changes some viewers mind to do better thinks and also behave in an improper way. The movie reviews are based on their understanding and usefulness of the information and the main theme adopted in the movies. The personal feelings are produced in the form of movie reviews. To analyze all such useful and un useful information is a tedious task. This research work utilizes the datamining techniques like Naïve Bayes, Support Vector Machine, Random Forest and Logistic Regression to find the pros and cons of the movie reviews. To visualize the feelings of the reviewers. This work identifies the best movie released and accepted based on the reviewer comments. Finally, the best algorithm is suggested by means of its accuracy and performance.

Naïve Bayes Algorithm, Decision Tree Methods, Support Vector Machine Method, Random Forest Algorithm