社交媒体上直接面向消费者的基因检测:YouTube用户评论的话题建模和情感分析。

IF 3.5 Q1 HEALTH CARE SCIENCES & SERVICES
JMIR infodemiology Pub Date : 2022-07-01 DOI:10.2196/38749
Philipp A Toussaint, Maximilian Renner, Sebastian Lins, Scott Thiebes, Ali Sunyaev
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引用次数: 0

摘要

背景:随着直接面向消费者(DTC)的基因检测能够自我负责地获取有关祖先、特征或健康的新信息,消费者经常转向社交媒体寻求帮助和讨论。YouTube是最大的视频社交媒体平台,提供了大量与DTC基因检测相关的视频。然而,这些视频评论部分的用户话语在很大程度上是未被探索的。目的:本研究旨在通过探讨YouTube上DTC基因检测相关视频的讨论话题和用户对这些视频的态度,解决对用户话语的了解不足的问题。方法:采用三步研究方法。首先,我们收集了YouTube上248个观看次数最多的DTC基因检测相关视频的元数据和评论。其次,我们使用词频分析、双元图分析和结构主题建模进行主题建模,以识别这些视频评论部分讨论的主题。最后,我们使用必应(二进制)、加拿大国家研究委员会(NRC)情感和9级情感分析来确定用户对这些DTC基因检测相关视频的态度,以及他们在评论中表达的态度。结果:我们从248个观看次数最多的DTC基因检测相关YouTube视频中收集了84,082条评论。通过主题建模,我们确定了6个流行的主题:(1)一般基因测试,(2)祖先测试,(3)关系测试,(4)健康和特征测试,(5)伦理问题,以及(6)YouTube视频反应。此外,我们的情绪分析表明强烈的积极情绪(期待,喜悦,惊喜和信任)和中立到积极的态度对DTC基因检测相关的视频。结论:通过本研究,我们展示了如何通过检查基于YouTube视频评论的主题和观点来识别用户对DTC基因检测的态度。从社交媒体上的用户话语来看,我们的研究结果表明,用户对DTC基因检测和相关社交媒体内容非常感兴趣。尽管如此,随着这个新兴市场的不断发展,服务提供商、内容提供商或监管机构可能仍然需要根据用户的兴趣和愿望调整他们的服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Direct-to-Consumer Genetic Testing on Social Media: Topic Modeling and Sentiment Analysis of YouTube Users' Comments.

Background: With direct-to-consumer (DTC) genetic testing enabling self-responsible access to novel information on ancestry, traits, or health, consumers often turn to social media for assistance and discussion. YouTube, the largest social media platform for videos, offers an abundance of DTC genetic testing-related videos. Nevertheless, user discourse in the comments sections of these videos is largely unexplored.

Objective: This study aims to address the lack of knowledge concerning user discourse in the comments sections of DTC genetic testing-related videos on YouTube by exploring topics discussed and users' attitudes toward these videos.

Methods: We employed a 3-step research approach. First, we collected metadata and comments of the 248 most viewed DTC genetic testing-related videos on YouTube. Second, we conducted topic modeling using word frequency analysis, bigram analysis, and structural topic modeling to identify topics discussed in the comments sections of those videos. Finally, we employed Bing (binary), National Research Council Canada (NRC) emotion, and 9-level sentiment analysis to identify users' attitudes toward these DTC genetic testing-related videos, as expressed in their comments.

Results: We collected 84,082 comments from the 248 most viewed DTC genetic testing-related YouTube videos. With topic modeling, we identified 6 prevailing topics on (1) general genetic testing, (2) ancestry testing, (3) relationship testing, (4) health and trait testing, (5) ethical concerns, and (6) YouTube video reaction. Further, our sentiment analysis indicates strong positive emotions (anticipation, joy, surprise, and trust) and a neutral-to-positive attitude toward DTC genetic testing-related videos.

Conclusions: With this study, we demonstrate how to identify users' attitudes on DTC genetic testing by examining topics and opinions based on YouTube video comments. Shedding light on user discourse on social media, our findings suggest that users are highly interested in DTC genetic testing and related social media content. Nonetheless, with this novel market constantly evolving, service providers, content providers, or regulatory authorities may still need to adapt their services to users' interests and desires.

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