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arXiv · 2109.09276

From None to Severe: Predicting Severity in Movie Scripts

Yigeng Zhang·Mahsa Shafaei·Fabio Gonzalez·Thamar Solorio
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Abstract

In this paper, we introduce the task of predicting severity of age-restricted aspects of movie content based solely on the dialogue script. We first investigate categorizing the ordinal severity of movies on 5 aspects: Sex, Violence, Profanity, Substance consumption, and Frightening scenes. The problem is handled using a siamese network-based multitask framework which concurrently improves the interpretability of the predictions. The experimental results show that our method outperforms the previous state-of-the-art model and provides useful information to interpret model predictions. The proposed dataset and source code are publicly available at our GitHub repository.

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Yigeng Zhang, Mahsa Shafaei, Fabio Gonzalez, Thamar Solorio. 2021-09-20. From None to Severe: Predicting Severity in Movie Scripts. https://arxiv.org/abs/2109.09276

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