评估健康教育数字平台的包容性和代表性:来自YouTube的证据
Krishna Pothugunta1, Xiao Liu2, Anjana Susarla1
1Michigan State University, East Lansing, MI, USA.
Journal of biomedical informatics
|June 16, 2024
概括
主持人人口统计学影响了医疗保健视频在YouTube上的受欢迎程度. 带有男性和白人主持人的视频往往会获得更多的浏览量,这凸显了在线健康信息传播中的潜在偏见.
科学领域:
- 数字健康数字健康
- 卫生沟通健康沟通
- 公平的机器学习
背景情况:
- 像YouTube这样的在线平台表现出明显的偏见,加剧了代表性不足的群体之间的差异.
- 评估在线健康信息的包容性和代表性至关重要,因为许多成年人因为健康问题而使用互联网.
研究的目的:
- 调查YouTube上的医疗保健视频内容的包含和代表性的偏见.
- 为了确定主持人人口统计是否会影响健康视频的受欢迎程度.
主要方法:
- 利用公平的机器学习,NLP和语音/面部识别来分析大量与糖尿病相关的YouTube视频.
- 使用回归模型来评估主持人人口统计和视频受欢迎程度 (平均每日观看数) 之间的关系.
主要成果:
- 语音和面部识别准确地预测了演讲者的人口统计数据 (性别,种族).
- 当面部看不到时,主持人性别显著影响了观点;男性主持人与更高的观点相关.
- 有白人和男性主持人的视频对观看次数产生了积极影响,而女性和非白人主持人也获得了高观看次数.
结论:
- 演讲者的人口统计数据显然影响了社交媒体上健康视频的平均每日浏览次数.
- 未来的研究应该探索短视频和频道级人气指标,以全面了解影响力.
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