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Collaborative Social Systems Lab
at Northeastern University
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.
  Learn about the lab:
  • ​Meet the team
  • Explore our research
  • Read our publications
  • View news coverage of our work
Latest News
10.21.21
“The Collective Intelligence of Remote Teams," MIT Sloan Management Review

5.07.21

“The Art Market Often Works in Secret. Here’s a Look Inside.,” The New York Times.

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10.06.20
“Zoom calls can be too formal. These alternatives encourage casual chatting,” Fast Company.

8.17.20
“Remote workers want to re-create those watercooler moments, virtually,” MIT Technology Review.

8.12.20
“Water cooler moments don’t have to disappear in the virtual workplace,” Quartz.
More News
​Recent Publications
Collective Intelligence in Human-AI Teams: A Bayesian Theory of Mind Approach. Westby, S. & Riedl, C. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (2023). arXiv:2208.11660 [cs], Github

Collective attention and collective intelligence: The role of hierarchy and team gender composition. Woolley, A.W., Chow, R., Mayo, A., Riedl, C., Chang, J. W. (2022). Organization Science, in press.

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.
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