The People's Choice: PAIRing User-Centered Design With Crowdsourcing To Combat Misinformation on TikTok

Abstract

Social Networking sites like Facebook, Twitter, YouTube, and TikTok have created a rampant increase in user-generated content online. Moderation and validation of misinformation on these platforms are still significant challenges. One approach to address misinformation on social media has been to crowdsource the validity of content through the platform users. However, research conducted on crowdsourced fact-checking has focused largely on traditional and text-based sources. In addition, it has yet to focus on user-centered design to understand how users of platforms would create tools to mitigate misinformation. This thesis addresses these knowledge gaps by understanding approaches to using crowdsourcing to combat misinformation on TikTok, the fastest-growing social networking site with over one billion monthly active users. By using TikTok as a case study, I conduct a thematic analysis of content on the platform to understand how users currently counter claims and misinformation and then conduct participatory design sessions with TikTok users to identify limitations, improvements, and potential solutions. Based on these findings, I present a set of design guidelines referred to as the PAIR approach that outline key considerations for a crowdsourcing platform combatting misinformation on a social networking site such as TikTok.