Fernandez-Luque Luis, Karlsen Randi, Melton Genevieve B
Northern Research Institute, Tromsø, Norway.
J Med Internet Res. 2012 Jan 31;14(1):e22. doi: 10.2196/jmir.1985.
Social media are becoming mainstream in the health domain. Despite the large volume of accurate and trustworthy health information available on social media platforms, finding good-quality health information can be difficult. Misleading health information can often be popular (eg, antivaccination videos) and therefore highly rated by general search engines. We believe that community wisdom about the quality of health information can be harnessed to help create tools for retrieving good-quality social media content.
To explore approaches for extracting metrics about authoritativeness in online health communities and how these metrics positively correlate with the quality of the content.
We designed a metric, called HealthTrust, that estimates the trustworthiness of social media content (eg, blog posts or videos) in a health community. The HealthTrust metric calculates reputation in an online health community based on link analysis. We used the metric to retrieve YouTube videos and channels about diabetes. In two different experiments, health consumers provided 427 ratings of 17 videos and professionals gave 162 ratings of 23 videos. In addition, two professionals reviewed 30 diabetes channels.
HealthTrust may be used for retrieving online videos on diabetes, since it performed better than YouTube Search in most cases. Overall, of 20 potential channels, HealthTrust's filtering allowed only 3 bad channels (15%) versus 8 (40%) on the YouTube list. Misleading and graphic videos (eg, featuring amputations) were more commonly found by YouTube Search than by searches based on HealthTrust. However, some videos from trusted sources had low HealthTrust scores, mostly from general health content providers, and therefore not highly connected in the diabetes community. When comparing video ratings from our reviewers, we found that HealthTrust achieved a positive and statistically significant correlation with professionals (Pearson r₁₀ = .65, P = .02) and a trend toward significance with health consumers (r₇ = .65, P = .06) with videos on hemoglobinA(1c), but it did not perform as well with diabetic foot videos.
The trust-based metric HealthTrust showed promising results when used to retrieve diabetes content from YouTube. Our research indicates that social network analysis may be used to identify trustworthy social media in health communities.
社交媒体正在成为健康领域的主流。尽管社交媒体平台上有大量准确且可靠的健康信息，但找到高质量的健康信息可能很困难。误导性的健康信息往往很受欢迎（例如反疫苗接种视频），因此在一般搜索引擎中获得的评分很高。我们认为，可以利用在线健康社区中关于健康信息质量的集体智慧来帮助创建检索高质量社交媒体内容的工具。
探索提取在线健康社区中权威性指标的方法，以及这些指标如何与内容质量呈正相关。
我们设计了一种名为HealthTrust的指标，用于评估健康社区中社交媒体内容（如博客文章或视频）的可信度。HealthTrust指标基于链接分析计算在线健康社区中的声誉。我们使用该指标检索有关糖尿病的YouTube视频和频道。在两项不同的实验中，健康消费者对17个视频给出了427个评分，专业人员对23个视频给出了162个评分。此外，两名专业人员对30个糖尿病频道进行了审查。
HealthTrust可用于检索有关糖尿病的在线视频，因为在大多数情况下它的表现优于YouTube搜索。总体而言，在20个潜在频道中，HealthTrust的筛选只允许3个不良频道（15%），而YouTube列表中有8个（40%）。YouTube搜索比基于HealthTrust的搜索更常找到误导性和有图片的视频（例如有截肢画面的视频）。然而，一些来自可靠来源的视频HealthTrust得分较低，大多来自一般健康内容提供者，因此在糖尿病社区中的关联度不高。在比较我们的审查人员给出的视频评分时，我们发现HealthTrust与专业人员的评分呈正相关且具有统计学意义（Pearson r₁₀ = 0.65，P = 0.02），与健康消费者对糖化血红蛋白视频的评分有显著相关趋势（r₇ = 0.65，P = 0.06），但在糖尿病足视频方面表现不佳。
基于信任的指标HealthTrust在用于从YouTube检索糖尿病内容时显示出了有前景的结果。我们的研究表明，社交网络分析可用于识别健康社区中值得信赖的社交媒体。
