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视频流网站上的同步评论揭示了电影观看中观众参与的核心结构。

Time-synchronic comments on video streaming website reveal core structures of audience engagement in movie viewing.

作者信息

Ni Wenjing, Coupé Christophe

机构信息

Department of Linguistics, School of Humanities, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.

Laboratoire Dynamique du Langage, UMR 5596-CNRS, Université Lyon 2, Lyon, France.

出版信息

Front Psychol. 2023 Jan 19;13:1040755. doi: 10.3389/fpsyg.2022.1040755. eCollection 2022.

Abstract

To what extent movie viewers are swept into a fictional world has long been pondered by psychologists and filmmakers. With the development of time-synchronic comments on online viewing platforms, we can now analyze viewers' immediate responses toward movies. In this study, we collected over 3 million Chinese time-synchronic comments from a video streaming website. We first assessed emotion and cognition-related word rates in these comments with the Simplified Chinese version of the Linguistic Inquiry and Word Count (SCLIWC) and applied time-series clustering to the word rates. Then Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) was conducted on the text to investigate the prevalent topics among the comments. We found different commenting behaviors in front of various movies and prototypical diachronic trajectories of the psychological engagement of the audience. We further identified how topics are discussed through time, and tried to account for viewer's engagement, considering successively movie genres, topics and movie content. Among other points, we finally discussed the challenge in explaining the trajectories of engagement and the disconnection with narrative content. Overall, our study provides a new perspective on using social media data to answer questions from psychology and film studies. It underscores the potential of time-synchronic comments as a resource for detecting real-time human responses to specific events.

摘要

电影观众在多大程度上被卷入虚构世界,长期以来一直是心理学家和电影制作人思考的问题。随着在线观看平台上实时同步评论的发展,我们现在可以分析观众对电影的即时反应。在这项研究中,我们从一个视频流网站收集了超过300万条中文实时同步评论。我们首先使用中文简化版的语言调查与字数统计工具(SCLIWC)评估这些评论中与情感和认知相关的词汇率,并将时间序列聚类应用于词汇率。然后,对文本进行基于密度的带噪声空间聚类应用层次方法(HDBSCAN),以调查评论中普遍存在的主题。我们发现了观众在不同电影前的不同评论行为以及观众心理参与的典型历时轨迹。我们进一步确定了主题随时间的讨论方式,并尝试依次考虑电影类型、主题和电影内容来解释观众的参与度。在其他要点中,我们最后讨论了解释参与轨迹以及与叙事内容脱节方面的挑战。总体而言,我们的研究为利用社交媒体数据回答心理学和电影研究问题提供了一个新视角。它强调了实时同步评论作为检测人类对特定事件实时反应资源的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/853a/9893864/38a075d629c5/fpsyg-13-1040755-g001.jpg

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