Analysing the Impact of Sentiment Analysis on Predicting Movie Success in Social Network Communities: A Review

Abstract

Abstract: Today’s online world was fully filled up with blogs, views, comments, and posts through various websites and social surfaces. Sentiment analysis has emerged as a valuable tool in the film industry for automatically categorizing the polarity of thoughts expressed in movie reviews. By analyzing language patterns, sentiment analysis can determine whether a review contains a positive or negative assessment of a particular movie. This approach allows for both objective and subjective methods to predict the success of a movie. With this analysis, it is possible to evaluate audience reactions and identify trends in movie reviews, which can be valuable for filmmakers and movie studios seeking to gauge public opinion and make informed decisions about future projects. In order to perform sentiment analysis on movie reviews, machine learning algorithms are usually applied after natural language processing techniques have been used to extract pertinent features from the text, such as sentimentbearing words and phrases. Objective methods use statistical and machine learning techniques to analyze past movie data, such as budget, genre, and release date, to predict box office revenues.