Reference Hub6
Prediction of Movie Success Using Sentimental Analysis and Data Mining

Prediction of Movie Success Using Sentimental Analysis and Data Mining

Meenu Vijarania, Ashima Gambhir, Deepthi Sehrawat, Swati Gupta
Copyright: © 2022 |Pages: 16
ISBN13: 9781799890126|ISBN10: 1799890120|ISBN13 Softcover: 9781799890133|EISBN13: 9781799890140
DOI: 10.4018/978-1-7998-9012-6.ch008
Cite Chapter Cite Chapter

MLA

Vijarania, Meenu, et al. "Prediction of Movie Success Using Sentimental Analysis and Data Mining." Applications of Computational Science in Artificial Intelligence, edited by Anand Nayyar, et al., IGI Global, 2022, pp. 174-189. https://doi.org/10.4018/978-1-7998-9012-6.ch008

APA

Vijarania, M., Gambhir, A., Sehrawat, D., & Gupta, S. (2022). Prediction of Movie Success Using Sentimental Analysis and Data Mining. In A. Nayyar, S. Kumar, & A. Agrawal (Eds.), Applications of Computational Science in Artificial Intelligence (pp. 174-189). IGI Global. https://doi.org/10.4018/978-1-7998-9012-6.ch008

Chicago

Vijarania, Meenu, et al. "Prediction of Movie Success Using Sentimental Analysis and Data Mining." In Applications of Computational Science in Artificial Intelligence, edited by Anand Nayyar, Sandeep Kumar, and Akshat Agrawal, 174-189. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-7998-9012-6.ch008

Export Reference

Mendeley
Favorite

Abstract

Movies have become a significant part of today's generation. In this chapter, the authors worked on data mining and ML techniques like random forest regression, decision tree regression, support vector regression, and predict the success of the movies on the basis of ratings from IMDb and data retrieved from comments on social media platforms. Based on ML techniques, the chapter develops a model that will predict movie success before the release of the movie and thereby decrease the risk. Twitter sentimental analysis is used to retrieve data from Twitter, and polarity and subjectivity of the movie is calculated based on the user reviews, and those retrieved data machine learning algorithms are used to predict the IMDb rating. A predictive model is developed by using three algorithms, decision tree regression, SVR, and random forest regression. The chapter compared the results using three different techniques to get the movie success prediction at a reasonable accuracy.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.