Explainable Neural Network analysis on Movie Success Prediction

Author:

Bhavesh Kumar S,Pande Sagar Dhanraj

Abstract

These days movies are one of the most important part of entertainment industry and back in the days you could see everyday people standing outside theatres, or watching movies in OTT platforms. But due to busy schedules not many people are watching every movie. They go over the internet and search for top rated movies and go to theatres. And creating a successful movie is no easy job. Thus, this study helps movie producers to consider what are the important factors that influence a movie to be successful.  this study applied neural network model to the IMDb dataset and then due to its complex nature in order to achieve the local explainability and global explainability for the enhanced analysis, study have used SHAP (Shapley additive explanations) to analysis.

Publisher

European Alliance for Innovation n.o.

Subject

Information Systems and Management,Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Software

Reference20 articles.

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3. You Jin Kim, Yun Gyung Cheong, and Jung Hoon Lee. 2019. Prediction of a Movie’s Success From Plot Summaries Using Deep Learning Models. In Proceedings of the Second Workshop on Storytelling, pages 127–135, Florence, Italy. Association for Computational Linguistics.

4. Sahu, S., Kumar, R., Long, H.V. et al. Early-production stage prediction of movies success using K-fold hybrid deep ensemble learning model. Multimed Tools Appl 82, 4031–4061 (2023).

5. Ni, Yuan, et al. "Movie Box Office Prediction Based on Multi-Model Ensembles." Information 13.6 (2022): 299.

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