Unveiling the Impact of Privacy-Preserving Policies in Crowd-based Misinformation Monitoring Program

In response to the pervasive dissemination of misinformation on social media platforms, various strategies have been explored by governments and social media companies to prevent and monitor its spread, including the democratization of misinformation monitoring. However, evaluating the impacts of these misinformation monitoring programs is crucial, given the significant threat to public opinion and societal stability. This paper evaluates the consequences of a privacy policy change within a crowd-based misinformation monitoring program, focusing on Twitter's Birdwatch initiative. Leveraging a regression discontinuity approach, we analyze the effects of the policy shift on content generated by the participants, examining both quantity and quality metrics. Our findings indicate that the privacy-preserving mechanism led to an increase in content frequency without impacting fact-checking activity. Additionally, we observe improvements in content neutrality, analytical thinking, and authenticity, alongside a reduction in negativity. This research contributes to the literature and practice of crowd-based programs and misinformation.