探索在线评论对票房收入的影响——基于多维度情感视角
Exploring the Impact of Online Reviews on Box Office Revenue—Based on Multi-Dimensional Emotional Perspective
DOI: 10.12677/MM.2023.135069, PDF,    科研立项经费支持
作者: 别春洋, 陶贻勇:安徽理工大学计算机科学与工程学院,安徽 淮南
关键词: 在线评论票房多维度情绪情感方差分位数回归Online Reviews Box Office Multi-Dimensional Sentiments Sentiment Variance Quantile Regression
摘要: 本文选取了2017~2021年的121,603条在线评论,将多属性态度理论引入到实证研究中,从多维度情感驱动的新视角考察在线评论对票房的影响。采用DTM (Dynamic Topic Models,动态主题模型)和情感挖掘技术从在线评论中提取特定维度的情感,然后使用分位数回归分析多维度情感对电影票房的影响。研究结果表明,三个维度的情感对电影票房具有正向促进作用(明星、类型和情节)。具体而言,明星对票房的影响呈现倒U型,情节对票房的影响随着分位数的上升而增加,类型对于票房的影响集中在中部的分位点。情感方差负向调节三个特定维度情绪对票房的影响。我们的研究丰富了关于网络评论和电影营销的实证研究,并基于实证结果提出了一些管理意义和实践见解。
Abstract: This paper selects 121,603 online reviews from 2017 to 2021, introduces multi-attribute attitude theory into empirical research, and examines the impact of online reviews on box office from a new perspective driven by multi-dimensional emotions. This paper uses DTM (Dynamic Topic Model) and sentiment mining technology to extract the sentiment of specific dimensions from online reviews, and then using quantile regression to analyze the impact of multi-dimensional sentiment on movie box office. The results of the study show that three dimensions of emotion have a positive effect on movie box office (star, genre and plot). Specifically, the influence of stars on box office presents an inverted U shape, the influence of plot on box office increases as the quantile rises, and the influence of genre on box office is concentrated in the middle quantile. Emotional variance negatively moderates the impact of three specific dimensions of emotion on box office. Our study enriches the empirical research on online reviews and movie marketing, and proposes some managerial implications and practical insights based on the empirical results.
文章引用:别春洋, 陶贻勇. 探索在线评论对票房收入的影响——基于多维度情感视角[J]. 现代管理, 2023, 13(5): 535-546. https://doi.org/10.12677/MM.2023.135069

参考文献

[1] 郝晓玲, 陈晓梦. 体验型产品消费行为的羊群效应及机理研究——基于电影行业消费行为的实证解释[J]. 中国管理科学, 2019, 27(11): 176-188.
[2] Zhang, D., Wu, P. and Wu, C. (2021) The Role of Key Online Reviews in Af-fecting Online Hotel Booking: An Empirical Investigation. Industrial Management and Data Systems, 122, 499-520. [Google Scholar] [CrossRef
[3] Ludwig, S., De Ruyter, K., Friedman, M., Brüggen, E.C., Wet-zels, M. and Pfann, G. (2013) More than Words: The Influence of Affective Content and Linguistic Style Matches in Online Reviews on Conversion Rates. Journal of Marketing, 77, 87-103. [Google Scholar] [CrossRef
[4] Li, X., Wu, C. and Mai, F. (2019) The Effect of Online Reviews on Prod-uct Sales: A Joint Sentiment-Topic Analysis. Information and Management, 56, 172-184. [Google Scholar] [CrossRef
[5] Wang, F., Liu, X. and Fang, E.E. (2015) User Reviews Variance, Critic Reviews Variance, and Product Sales: An Exploration of Customer Breadth and Depth Effects. Journal of Retailing, 91, 372-389. [Google Scholar] [CrossRef
[6] Duan, W., Gu, B. and Whinston, A.B. (2008) The Dynamics of Online Word-of-Mouth and Product Sales—An Empirical Investigation of the Movie Industry. Journal of Retailing, 84, 233-242. [Google Scholar] [CrossRef
[7] 石文华, 钟碧园, 张绮. 在线影评和在线短评对票房收入影响的比较研究[J]. 中国管理科学, 2017(10): 162-170.
[8] Liu, Q.B. and Karahanna, E. (2017) The Dark Side of Re-views: The Swaying Effects of Online Product Reviews on Attribute Preference Construction. MIS Quarterly, 41, 427-448. [Google Scholar] [CrossRef
[9] Ma, H., Kim, J.M. and Lee, E. (2019) Analyzing Dy-namic Review Manipulation and Its Impact on Movie Box Office Revenue. Electronic Commerce Research and Applica-tions, 35, Article ID: 100840. [Google Scholar] [CrossRef
[10] Zhang, Z., Li, X. and Chen, Y. (2012) Deciphering Word-of-Mouth in Social Media: Text-Based Metrics of Consumer Reviews. ACM Transactions on Management In-formation Systems, 3, 1-23. [Google Scholar] [CrossRef
[11] Hu, N., Koh, N.S. and Reddy, S.K. (2014) Ratings Lead You to the Product, Reviews Help You Clinch It? The Mediating Role of Online Review Sentiments on Product Sales. Decision Support Systems, 57, 42-53. [Google Scholar] [CrossRef
[12] Xu, D., Ye, Q., Hong, H. and Sun, F. (2022) Emotions for Atten-tion in Online Consumer Reviews: The Moderated Mediating Role of Review Helpfulness. Industrial Management and Data Systems, 122, 729-751. [Google Scholar] [CrossRef
[13] Kraft, F.B., Granbois, D.H. and Summers, J.O. (1973) Brand Evaluation and Brand Choice: A Longitudinal Study. Journal of Marketing Research, 10, 235-241. [Google Scholar] [CrossRef
[14] Jiménez, F.R. and Mendoza, N.A. (2013) Too Popular to Ig-nore: The Influence of Online Reviews on Purchase Intentions of Search and Experience Products. Journal of Interactive Marketing, 27, 226-235. [Google Scholar] [CrossRef
[15] Sabatino, S., Frangopol, D.M. and Dong, Y. (2015) Sustainabil-ity-Informed Maintenance Optimization of Highway Bridges Considering Multi-Attribute Utility and Risk Attitude. En-gineering Structures, 102, 310-321. [Google Scholar] [CrossRef
[16] Tirunillai, S., and Tellis, G.J. (2014) Mining Marketing Meaning from Online Chatter: Strategic Brand Analysis of Big Data Using Latent Dirichlet Allocation. Journal of Mar-keting Research, 51, 463-479. [Google Scholar] [CrossRef
[17] Blei, D.M., Ng, A.Y. and Jordan, M.I. (2003) Latent Dirichlet Allocation. Journal of Machine Learning Research, 3, 993-1022.
[18] Manek, A.S., Shenoy, P.D. and Mohan, M.C. (2017) Aspect Term Extraction for Sentiment Analysis in Large Movie Reviews Using Gini Index Feature Selection Method and SVM Classifier. World Wide Web, 20, 135-154. [Google Scholar] [CrossRef
[19] Sha, H., Hasan, M.A., Mohler, G. and Brantingham, P.J. (2020) Dynamic Topic Modeling of the COVID-19 Twitter Narrative among US Governors and Cabinet Executives. arXiv pre-print arXiv: 2004.11692. https://arxiv.org/abs/2004.11692
[20] Yao, F. and Wang, Y. (2020) Tracking Urban Geo-Topics Based on Dynamic Topic Model. Computers, Environment and Urban Systems, 79, Article ID: 101419. [Google Scholar] [CrossRef
[21] Koenker, R. (2004) Quantreg: An R Package for Quantile Regression and Related Methods. The Comprehensive R Archive Net-Work Website.