Keywords
Group awareness, Computer Supported Cooperative Work (CSCW), sentiment analysis, Artificial Intelligence, Machine Learning, Federated Learning.Context
The proliferation of home officing and other teleworking practices has deeply transformed the way people collaborate in the workplace, leading to a proliferation of digital platforms (Teams, Zoom, Jira, etc.) and a scattering of information across such platforms. This evolution brings with it new challenges: loss of team cohesion, isolation, difficulty in tracking project progress, and increased risk of disengagement or psychological distress among employees.This PhD thesis will be conducted under the direction of Manuele Kirsch Pinheiro (Université Paris 1 Panthéon-Sorbonne), with Luiz Angelo Steffenel (Université de Reims Champagne-Ardenne) as codirector.
Thesis goals
The thesis stands at the crossroads of two research fields: Computer Supported Cooperative Work (CSCW), and its notion of group awareness, and Artificial Intelligence, with its Machine Learning techniques. The thesis aims at:
- Proposing AI and Machine Learning models to extract, from multiplatform activity traces, relevant group awareness information;
- Detecting early signs of disengagement or distress among team members;
- Designing personalized group awareness information dissemination and alert mechanisms, respecting privacy (RGPD, AI Act), to reinforce team cohesion and well-being;
- Exploring Federated Learning and incremental learning approaches to adapt models to each collaborative context.
