Linguistic factors in digital entertainment success: How review readability affects movie outcomes on Chinese online platforms

IF 2.8 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing Pub Date : 2025-01-01 DOI:10.1016/j.entcom.2024.100911

Xi Fang , Aihua Han , Yifang Luo , WonHo Choi , Fan Zhang

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引用次数: 0

Abstract

Online movie reviews play a crucial role in shaping the digital entertainment landscape by influencing consumer decision-making. However, little research has investigated how the readability of these reviews impacts film performance. This paper examines the relationship between the readability of reviews on online platforms and movie market outcomes, including box office revenue, audience ratings, and popularity. We collected a dataset of 116,771 Chinese-language reviews from the Douban platform for 224 movies released in China between January 2019 and September 2022. Using natural language processing techniques, we calculated various readability metrics for each movie’s reviews. We then analyzed how these readability scores correlated with the movies’ economic and ratings performance. The results show that movies with more readable reviews tend to have higher box office returns, better audience reviews, and larger viewership. However, this effect is weakened when movies receive coverage from more authoritative official media sources or when the movies are not entertaining enough. We also find that the number of “useful” upvotes on reviews partially mediates the relationship between readability and movie outcomes. This study contributes novel insights into how the linguistic features of user-generated content can impact the success of digital entertainment products. The findings can help platforms design more effective review systems and assist studios in marketing movies online. Future work could extend this approach to other domains like book reviews or video game feedback.

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数字娱乐成功的语言因素：评论可读性如何影响中国在线平台上的电影结果

在线电影评论通过影响消费者的决策，在塑造数字娱乐格局方面发挥着至关重要的作用。然而，很少有研究调查这些评论的可读性如何影响电影的表现。本文研究了在线平台评论的可读性与电影市场结果（包括票房收入、收视率和受欢迎程度）之间的关系。我们从豆瓣平台收集了2019年1月至2022年9月期间在中国上映的224部电影的116,771篇中文评论的数据集。使用自然语言处理技术，我们计算了每部电影评论的各种可读性指标。然后，我们分析了这些可读性分数与电影的经济和评级表现之间的关系。结果表明，影评可读性强的电影往往有更高的票房回报、更好的观众评价和更大的观众群。然而，当电影获得更权威的官方媒体报道或电影不够娱乐时，这种效果就会减弱。我们还发现，评论中“有用的”赞的数量部分地中介了可读性和电影结果之间的关系。这项研究对用户生成内容的语言特征如何影响数字娱乐产品的成功提供了新颖的见解。这些发现可以帮助平台设计更有效的评论系统，并帮助电影公司在线营销电影。未来的工作可以将这种方法扩展到其他领域，如书评或电子游戏反馈。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Entertainment Computing Computer Science-Human-Computer Interaction

CiteScore

5.90

自引率

7.10%

发文量

期刊介绍： Entertainment Computing publishes original, peer-reviewed research articles and serves as a forum for stimulating and disseminating innovative research ideas, emerging technologies, empirical investigations, state-of-the-art methods and tools in all aspects of digital entertainment, new media, entertainment computing, gaming, robotics, toys and applications among researchers, engineers, social scientists, artists and practitioners. Theoretical, technical, empirical, survey articles and case studies are all appropriate to the journal.