Movie Success Prediction from Movie Trailer Engagement and Sentiment Analysis
- Title
- Movie Success Prediction from Movie Trailer Engagement and Sentiment Analysis
- Creator
- Emmanuvel A.; Bhagat V.; Jacob L.
- Description
- The diverse movie industry faces many challenges in the promotion of the product across different demographics. Movie trailer engagements provide valuable information about how the audience perceives the movie. This information can be used to predict the success of the upcoming movie before it gets released. The previous research works were mainly concentrating on Hindi language movies to predict success. The current research paper includes the success prediction of movies other than Hindi. This paper aims to analyze various Machine Learning models performance and select the best performing model to predict movie success. The developed model can efficiently classify successful and unsuccessful movies. For the current research, the data is collected from various sources through web scrapping and API calls in Sacnilk, The Movie Database (TMDB), YouTube, and Twitter. Different machine learning classification models such as Random Forest, Logistic Regression, KNN, and Gaussian Nae Bayes are tested to develop the best-performing prediction model. This research can help moviemakers to understand the popularity of the movie among the viewers and decide on an efficient promotional strategy to make the movie more successful. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
- Source
- Lecture Notes in Networks and Systems, Vol-290, pp. 385-393.
- Date
- 2021-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- E-word of mouth; Machine learning; Movie trailer engagement; Predictive analysis; Sentiment analysis; Web scraping
- Coverage
- Emmanuvel A., CHRIST (Deemed to be University), Lavasa, Pune, India; Bhagat V., CHRIST (Deemed to be University), Lavasa, Pune, India; Jacob L., CHRIST (Deemed to be University), Lavasa, Pune, India
- Rights
- Restricted Access
- Relation
- ISSN: 23673370; ISBN: 978-981164485-6
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Emmanuvel A.; Bhagat V.; Jacob L., “Movie Success Prediction from Movie Trailer Engagement and Sentiment Analysis,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/20597.