Abstract: The main part of information gathering is to find out what other people think. In case of movies, the movie reviews can provide an in-depth and detailed understanding of the movie and can help decide whether it is worth watching or not. However, with the growing amount of data in reviews, it is quite prudent to automate the process, saving a lot of time. Sentiment analysis is an important field of study in machine learning that practically deals with extracting useful information of subjects from the textual reviews. The sentiment analysis is closely related to Natural Language Processing (NLP) and text mining. It is used to determine the sentiments of the reviewer in regard to various topics or the overall polarity of the review. In case of movie reviews, along with giving a rating in numeric to a movie, they can give us information on the approval or the disapproval of a movie quantitatively. A collection of those information then gives us a comprehensive qualitative understanding on different facets of the movie. Since human language is complex, we face many kinds of challenges during opinion mining from movie reviews which might leads us to situations where a positive word has a negative connotation and vice versa.
Keywords: Machine Learning, Natural Language Processing, Text Mining, Opinion Mining, Analysis of Sentiments, Extracting Information.
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DOI:
10.17148/IJARCCE.2022.11348
