The THEMIS.COG project is aimed at Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups. THEMIS.COG will provide 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 will use 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.

• Main THEMIS.COG project page
• Official Digging Data project page

• Jesse Hoey
• Mei Nagappan
• Kimberley B. Rogers (Dartmouth College, USA)
• Tobias Schroeder (Potsdam Univ. of Applied Sciences, Germany)

• Transatlantic Partnership Digging into Data Challenge
• NSERC
• SSHRC