The project seeks to develop design principles for social computing applications in which knowledge is produced by large, loosely coordinated groups of people. The research will be carried out by an inter-disciplinary team that brings together expertise from computing and information science with the social sciences; perspectives from all of these areas will be crucial to developing the next generation of large-scale collaborative information systems on the Internet. A particular focus of the research will be on phenomena that affect the quality of information and discussion in these settings, including deception and the kinds of opinion dynamics that lead to polarization. The research will offer new analysis techniques and computational models for understanding such phenomena, drawing on novel styles of investigation involving large-scale datasets of social interaction and social network activity. Building on this, the research will also formulate design principles (based on ideas from intelligent task routing and games with a purpose) to enable creators of social computing applications to design for particular outcomes in the presence of complex underlying social phenomena.
The project is motivated by a profound transformation taking place in the way knowledge is produced and shared; in particular, the way it emerges in a "bottom-up" manner from global social networks that largely self-organize online. This raises profound challenges: at a time when a large proportion of Americans turn first to Internet sources for information about politics, health, commerce, and education, there is still very little understanding among the public as well as within the research community of how to deal with deception and misinformation online, or how to prevent online communities from falling into conflict and polarization. Through its focus on design principles and on these challenges, the project will attempt to create more effective means of online discourse and knowledge production.
