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COVID-19’s Impact on the Box Office: Machine Learning and Difference-in-Difference

2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)(2021)

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Abstract
As COVID-19 continues to spread around the world, and non-pharmacological interventions (NPIs) continue to be strengthened, the impact of COVID-19 on the film industry has not yet been clearly quantified. In this study, the Difference-in-Difference model is used to quantify the impact of the COVID-19 pandemic on the box office. Results indicate that the COVID-19 pandemic has a significant negative effect on the daily global box office. Additionally, based on a research dataset containing information on movies and COVID-19, ten machine learning methods were used to build a prediction model of the cumulative global box office. The experimental results showed that Extremely Randomized Trees had the best predictive performance, and it was found that COVID-19 features helped improve the predictive performance of several models.
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Key words
COVID-19,Analytical models,Solid modeling,Pandemics,Statistical analysis,Entertainment industry,Predictive models
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