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A social media phenomenon that has received limited research attention is the advent and propagation of viral online challenges. Several of these challenges entail self-harming behavior, which, combined with their viral nature, poses physical and psychological risks for both participants and viewers. The objective of this study is to identify the nature of what people post about the social media challenges that vary in their level of risk. To do so, we conducted a qualitative analysis of three viral social media challenges, the Blue Whale, Tide Pod, and Ice Bucket challenges, based on 180 YouTube videos, 3,607 comments on those YouTube videos, and 450 Twitter posts. We identified common themes across the YouTube videos, comments, and Twitter posts: (1) promoting education and awareness, (2) criticizing the participants, (3) providing detailed information about the participants, (4) giving viewers a tutorial on how to participate, and (5) attempting to understand this seemingly senseless online behavior. We used social norm theory to discuss what leads people to post about the challenges and how posts intended to raise awareness about harmful challenges could potentially create a contagion effect by spreading knowledge about them, thereby increasing participation. Finally, we proposed design implications that could potentially minimize the risks and propagation of harmful social media challenges. 

The use of automation is prevalent in almost every aspect of modern life, and since its inception researchers have been investigating trust in automation. There are many methods of measuring trust. Given that trust means different things to different people and by nature is subjective, most methods are subjective survey assessments (Freedy, DeVisser, Weltman, & Coeyman, 2007; Jian, Bisantz, & Drury, 2000). Many studies have investigated how the reliability of an automated agent or the level of automation changes subjective trust in the automation (Dixon & Wickens, 2006; Du, Zhang, & Yang, 2018; Khasawneh, Rogers, Bertrand, Madathil, & Gramopadhye, 2019; Rogers, Khasawneh, Bertrand, & Madathil, 2017).