The THEMIS.COG project is aimed at Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups. THEMIS.COG provides new theoretical insights into the dynamics of self-organized collaborations, in which people come together to work on a common problem, without prompting by a third party. Understanding the social forces behind self-organized collaboration is increasingly important in today's society. Technological and social innovations are increasingly generated through informal, distributed processes of collaboration, rather than in formal, hierarchical organizations. Our work uses a data-driven approach to explore the social and psychological mechanisms that motivate self-organized collaborations and determine their likelihood of success or failure, focusing on the example of open, collaborative software development in online collaborative networks (OCNs) like GitHub.



Two paper awards in 2017:

  1. American Sociological Association Section on Social Psychology, Outstanding Recent Contribution in Social Psychology Award.
  2. American Sociological Association Section on Mathematical Sociology, Outstanding Article Publication Award.
Both awards are for the paper: Tobias Schroeder, Jesse Hoey, and Kimberly B. Rogers. "Modeling Dynamic Identities and Uncertainty in Social Interactions: Bayesian Affect Control Theory." American Sociological Review 81(4): 828-855, 2016. This paper describes the theoretical basis of the Themis.Cog project.

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