Mining Public Voices: Analyzing Suicide-Related Thoughts and Behaviors in YouTube Videos and Comments Using Topic Modeling.

Hwayeon Danielle Shin, Jaejun Lee, Iman Kassam, Federica Guccini
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Abstract

YouTube has become a common platform for sharing difficult experiences and sensitive information, including suicide-related thoughts and behaviors. This study analyzes YouTube videos and their comments using topic modeling to explore the common themes discussed within the online community. Our findings show that these videos and comments not only focus on personal stories but also provide encouragement and healthcare-related information, highlighting social media's role in health promotion and peer support. Given that millions of people use various social media platforms to discuss a wide range of topics, these platforms serve as a rich source of data. As such, YouTube videos and comments offer health services researchers a valuable source of public opinion data, providing insights into societal attitudes and perceptions that may differ from those collected through traditional research methods.

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挖掘公众声音:使用主题建模分析YouTube视频和评论中的自杀相关思想和行为。
YouTube已经成为分享痛苦经历和敏感信息的共同平台,包括与自杀有关的想法和行为。本研究使用主题模型分析YouTube视频及其评论,以探索在线社区中讨论的共同主题。我们的研究结果表明,这些视频和评论不仅关注个人故事,还提供鼓励和医疗保健相关信息,突出了社交媒体在健康促进和同伴支持方面的作用。鉴于数百万人使用各种社交媒体平台讨论广泛的话题,这些平台可以作为丰富的数据来源。因此,YouTube视频和评论为卫生服务研究人员提供了一个宝贵的公众舆论数据来源,提供了对社会态度和看法的见解,这些看法可能不同于通过传统研究方法收集的结果。
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