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Computer Science > Human-Computer Interaction

arXiv:2506.10932 (cs)
[Submitted on 12 Jun 2025 (v1) , last revised 18 Jun 2025 (this version, v2)]

Title: Video-Mediated Emotion Disclosure: Expressions of Fear, Sadness, and Joy by People with Schizophrenia on YouTube

Title: 视频中介的情感宣泄:精神分裂症患者在YouTube上表达恐惧、悲伤和喜悦

Authors:Jiaying Lizzy Liu, Yan Zhang
Abstract: Individuals with schizophrenia frequently experience intense emotions and often turn to vlogging as a medium for emotional expression. While previous research has predominantly focused on text based disclosure, little is known about how individuals construct narratives around emotions and emotional experiences in video blogs. Our study addresses this gap by analyzing 200 YouTube videos created by individuals with schizophrenia. Drawing on media research and self presentation theories, we developed a visual analysis framework to disentangle these videos. Our analysis revealed diverse practices of emotion disclosure through both verbal and visual channels, highlighting the dynamic interplay between these modes of expression. We found that the deliberate construction of visual elements, including environmental settings and specific aesthetic choices, appears to foster more supportive and engaged viewer responses. These findings underscore the need for future large scale quantitative research examining how visual features shape video mediated communication on social media platforms. Such investigations would inform the development of care centered video sharing platforms that better support individuals managing illness experiences.
Abstract: 精神分裂症患者常常经历强烈的情绪,并经常转向视频博客作为情感表达的媒介。尽管以往的研究主要集中在基于文本的披露上,但对于个人如何在视频博客中围绕情绪和情感体验构建叙述知之甚少。我们的研究通过分析由精神分裂症患者创建的200个YouTube视频填补了这一空白。借鉴媒体研究和自我展示理论,我们开发了一个视觉分析框架来剖析这些视频。我们的分析揭示了通过口头和视觉渠道进行情绪披露的多样化实践,突显了这些表达模式之间的动态互动。我们发现,刻意构建视觉元素(包括环境设置和特定的美学选择)似乎会促进更支持性和参与度更高的观众反应。这些发现强调了未来大规模定量研究的必要性,以探讨视觉特征如何影响社交媒体平台上的视频中介交流。此类研究将有助于开发以护理为中心的视频共享平台,更好地支持管理疾病体验的个体。
Comments: 10 pages
Subjects: Human-Computer Interaction (cs.HC) ; Computers and Society (cs.CY); Multimedia (cs.MM)
Cite as: arXiv:2506.10932 [cs.HC]
  (or arXiv:2506.10932v2 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2506.10932
arXiv-issued DOI via DataCite
Journal reference: ASIS&T 2025

Submission history

From: Jiaying Liu [view email]
[v1] Thu, 12 Jun 2025 17:39:54 UTC (558 KB)
[v2] Wed, 18 Jun 2025 22:19:28 UTC (559 KB)
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