2019/08/21 by Mahsa Shafaei, Niloofar Safi Samghabadi, Shafaei, Mahsa +5 · 1 citation
Arts and Humanities · Computer Science · Social Sciences · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Hate Speech and Cyberbullying Detection #Machine Learning (cs.LG) #Media Influence and Politics #South Asian Cinema and Culture
paper · pdf · doi:10.48550/arxiv.1908.07819
openalex publication_date 2019/08/21 · openalex created_date 2019/08/29 · openalex updated_date 2026/07/28
The film culture has grown tremendously in recent years. The large number of streaming services put films as one of the most convenient forms of entertainment in today's world. Films can help us learn and inspire societal change. But they can also negatively affect viewers. In this paper, our goal is to predict the suitability of the movie content for children and young adults based on scripts. The criterion that we use to measure suitability is the MPAA rating that is specifically designed for this purpose. We propose an RNN based architecture with attention that jointly models the genre and the emotions in the script to predict the MPAA rating. We achieve 78% weighted F1-score for the classification model that outperforms the traditional machine learning method by 6%.