Description
This Master 2 internship aims to develop and evaluate algorithms for longitudinal detection of contributor teams on Wikipedia.
The challenge is twofold: on the technical level, it involves designing temporal graph clustering methods capable of tracking the coherent evolution of communities over time; on the application level, these methods must enable analysis of collaborative dynamics on Wikipedia by integrating organizational metrics from management science.
Wikipedia, with over 50 active language versions and millions of contributors, constitutes a privileged observation field for understanding how contributor teams form, evolve, and coordinate within editorial projects.
The algorithms will be evaluated on academic benchmarks and then applied to real Wikipedia projects to characterize the formation, evolution, and dissolution of editorial teams.
The internship will focus on implementing and evaluating the Spatio-Temporal Graph Laplacian algorithm, comparing it to baseline methods, and characterizing detected communities using organizational metrics (internal cohesion, collective viability, collaborative effectiveness, core-periphery structure).
An essential objective is producing a scientific article for an international conference and releasing all developed code as open source.
This internship is part of the PEPR eNSEMBLE - CONGRATS project (COllectives for kNowledge pRoduction mAnagement That Scale).
Full description of the /app/share//f77f1efd-2add--81c3-b43
Profile
We are seeking a Master 2 Research student with the following skills:
Starting date
-03-02