The Collaborative Social Systems Lab, directed by Christoph Riedl, explores collaboration in distributed environments: how can individuals solve challenging global tasks in social networks from only local, distributed interactions? We use agent-based modeling, conduct lab and field experiments, and analyze large datasets to study how networked interactions influence human behavior, strategies, and success.
“The Art Market Often Works in Secret. Here’s a Look Inside.,” The New York Times.
“Zoom calls can be too formal. These alternatives encourage casual chatting,” Fast Company.
“Remote workers want to re-create those watercooler moments, virtually,” MIT Technology Review.
“Water cooler moments don’t have to disappear in the virtual workplace,” Quartz.
Quantifying Collective Intelligence in Human Groups. Riedl, C., Kim, Y.J., Gupta, P., Malone, T.W., Woolley, A.W. (2021). Proceedings of the National Academy of Sciences, 118 (21) e2005737118.
Online Mingling: Supporting Ad Hoc, Private Conversations at Virtual Conferences (with and Thomas W. Malone). Song, J., Riedl, C., Malone, T.W. (2021). Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '21), presentation video.
Avoiding the Bullies: Resilience of Cooperation among
Unequals. Foley, M., Smead, R., Forber, P., Riedl, C. (2021). PLoS Computational Biology, 17(4): e1008847, replication data.
Incentives, competition, and inequality in markets for creative production. Balietti, S., Riedl, C. (2021). Research Policy, 50(4), 104212. Replication data.
Spite is Contagious in Dynamic Networks. Fulker, Z., Forber, P., Smead, R., Riedl, C. (2021). Nature Communications, 12(260). Replication data, open access PDF.