Chae Seung Woo, Hara Noriko, Shiroiya Harshit Rakesh, Chen Janice, Ogihara Ellen
Department of Journalism and Creative Media Industries, College of Media and Communication, Texas Tech University, Lubbock, Texas, United States of America.
The Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, Indiana, United States of America.
PLoS One. 2024 Dec 20;19(12):e0313857. doi: 10.1371/journal.pone.0313857. eCollection 2024.
This study explores COVID-19 communication between medical experts who upload YouTube videos related to health/medicine (hereinafter medical YouTubers) and their viewers. We investigated three specific elements: (1) how medical YouTubers' use of words related to analytical thinking is associated with their viewers' engagement, (2) how medical YouTubers' use of different types of emotion is associated with their viewers' engagement, and (3) the emotional alignment between medical YouTubers and their viewers. We collected 194 COVID-related video transcripts from five YouTube channels and 375,284 comments from those videos. We employed natural language processing to analyze the linguistic and emotional dimensions of these two text sets including analytical thinking, positive emotion, and negative emotion, the last of which was divided into anxiety, anger, and sadness. Additionally, three metrics provided by YouTube-the number of views, likes, and comments-were used as proxies representing user engagement. Our regression analysis results displayed that the medical YouTubers' analytical thinking was positively associated with the number of views. Regarding emotion, anxiety was positively correlated with the number of likes and comments, while both positive emotion and anger were negatively associated with the number of views. Finally, both positive and negative emotions of medical YouTubers were found to be positively correlated with the corresponding emotions of their viewers. Theoretical and practical implications of these findings are discussed within the context of COVID-19.
本研究探讨了上传与健康/医学相关YouTube视频的医学专家(以下简称医学YouTube博主)与他们的观众之间关于新冠疫情的交流。我们调查了三个具体因素:(1)医学YouTube博主对与分析性思维相关词汇的使用如何与其观众的参与度相关联;(2)医学YouTube博主对不同类型情感的使用如何与其观众的参与度相关联;(3)医学YouTube博主与其观众之间的情感一致性。我们从五个YouTube频道收集了194份与新冠疫情相关的视频文字记录以及这些视频下的375,284条评论。我们运用自然语言处理技术来分析这两组文本在语言和情感方面的维度,包括分析性思维、积极情感和消极情感,其中消极情感又分为焦虑、愤怒和悲伤。此外,YouTube提供的三个指标——观看次数、点赞数和评论数——被用作代表用户参与度的代理指标。我们的回归分析结果显示,医学YouTube博主的分析性思维与观看次数呈正相关。在情感方面,焦虑与点赞数和评论数呈正相关,而积极情感和愤怒与观看次数呈负相关。最后,发现医学YouTube博主的积极情感和消极情感都与他们观众的相应情感呈正相关。我们在新冠疫情的背景下讨论了这些发现的理论和实践意义。