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Facebook announced a community review program in December 2019 and Twitter launched a community-based platform to address misinformation, called Birdwatch, in January 2021. We provide an overview of the potential affordances of such community based approaches to content moderation based on past research. While our analysis generally supports a community-based approach to content moderation, it also warns against potential pitfalls, particularly when the implementation of the new infrastructures does not promote diversity. We call for more multidisciplinary research utilizing methods from complex systems studies, behavioural sociology, and computational social science to advance the research on crowd-based content moderation.
The Turing test aimed to recognize the behavior of a human from that of a computer algorithm. Such challenge is more relevant than ever in todays social media context, where limited attention and technology constrain the expressive power of humans, w
The increasing pervasiveness of social media creates new opportunities to study human social behavior, while challenging our capability to analyze their massive data streams. One of the emerging tasks is to distinguish between different kinds of acti
Social media, the modern marketplace of ideas, is vulnerable to manipulation. Deceptive inauthentic actors impersonate humans to amplify misinformation and influence public opinions. Little is known about the large-scale consequences of such operatio
Social media sites are information marketplaces, where users produce and consume a wide variety of information and ideas. In these sites, users typically choose their information sources, which in turn determine what specific information they receive
The massive spread of digital misinformation has been identified as a major global risk and has been alleged to influence elections and threaten democracies. Communication, cognitive, social, and computer scientists are engaged in efforts to study th