June 2024 How are PreLaunch online movie reviews related to box office revenues?
Tianyu Guan, Jason Ho, Robert Krider, Jiguo Cao, Andrew Fogg
Author Affiliations +
Ann. Appl. Stat. 18(2): 1686-1708 (June 2024). DOI: 10.1214/23-AOAS1854

Abstract

This paper studies the dynamic patterns of the prelaunch online movie reviews, or movie electronic word-of-mouth (eWOM), over time and investigates their relations to the subsequent box office revenues. The volume and valence of prelaunch eWOM have been shown to be early indicators of strong or weak box office. The time patterns of prelaunch eWOM evolution, which are essentially functional data, on the other hand, tend to be overlooked. We apply the functional principal component analysis, a dimension reduction technique in functional data analysis, to analyze the dynamic patterns of various quantile trajectories of the movie eWOM, instead of directly studying the whole eWOM functional data. The functional principal component (FPC) scores of quantile trajectories at various quantile levels are used to predict the box office revenues. We use the sparse group lasso method to select the quantile levels and individual FPC scores that make significant contributions to the prediction of box office revenues. The results show that compared with other measures, such as valence and variance, the top-end quantiles would be a better measure in capturing the relations between the prelaunch product ratings time pattern and launch sales.

Funding Statement

This research is supported by the Discovery grants (RGPIN-2023-04057 to J. Cao and RGPIN-2022-05140 to T. Guan) from the Natural Sciences and Engineering Research Council of Canada (NSERC).

Acknowledgments

The authors would like to thank the Editor, the Associate Editor and two anonymous referees for many insightful comments. These comments are very helpful for us to improve our work.

T. Guan is an Assistant Professor at the Department of Mathematics and Statistics at York University. J. Ho is an Associate Professor at Beedie School of Business, Simon Fraser University. R. Krider is a Professor Emeritus at Beedie School of Business, Simon Fraser University. J. Cao is a Professor at the Department of Statistics and Actuarial Science at Simon Fraser University. A. Fogg is an Engineering Manager in the Advanced Development group at Roku, Inc.

J. Cao is the corresponding author for this article.

Citation

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Tianyu Guan. Jason Ho. Robert Krider. Jiguo Cao. Andrew Fogg. "How are PreLaunch online movie reviews related to box office revenues?." Ann. Appl. Stat. 18 (2) 1686 - 1708, June 2024. https://doi.org/10.1214/23-AOAS1854

Information

Received: 1 June 2022; Revised: 1 November 2023; Published: June 2024
First available in Project Euclid: 5 April 2024

Digital Object Identifier: 10.1214/23-AOAS1854

Keywords: Electronic word of mouth , Functional data analysis , functional principal component analysis , quantile functions , Variable selection

Rights: Copyright © 2024 Institute of Mathematical Statistics

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Vol.18 • No. 2 • June 2024
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