Équipe de recherche :Research Team:
Numérique, Organisation et Société (NOS)Digital Technologies, Organization and Society (DTOS)
Laboratoire :Laboratory:
Institut Interdisciplinaire de l’Innovation (i3)Interdisciplinary Institute of Innovation (i3)
Département :Department:
Sciences Économiques et Sociales (SES)Economics and Social Sciences (SES)
Mathilde Abel is an associate professor of economic sociology at Télécom Paris – Institut Polytechnique de Paris, where she is affiliated with i3 – the Interdisciplinary Institute for Innovation. Her work combines economic sociology and political economy with approaches from computational social science. She holds a Ph.D. in economics from Sorbonne Nouvelle University; her dissertation focused on the study of digital intermediation, coordination, and distributed cognition, with the aim of understanding how digital platforms are reshaping economic relationships and power dynamics. Following her dissertation, she also served as a postdoctoral researcher at ENSAE within the CREST research unit.
Research activities:
My research focuses on the political economy of digital platforms, particularly platform work, data labor, algorithmic intermediation, and cognitive asymmetries. I seek to understand how platforms organize markets and labor, how algorithmic systems affect workers’ autonomy and capacity for action, and how workers adapt to these forms of coordination. I combine qualitative research, theoretical analysis, and computational methods—particularly natural language processing (NLP)—to analyze data generated by workers. I am currently working on the ANR VOLI (Voices from Online Labor) project and conducting research on platform delivery workers as well as on content posted on YouTube by platform drivers. I am also a member of the DiPLab research group and the Computational Social Sciences (CSS) group at the Institut Polytechnique de Paris.
Teaching activities
My teaching also draws on sociology, institutional economics, and computational social science. These courses focus both on the social and political effects of digital technologies and on the methods used to study them empirically. They combine discussions of research, data analysis, and training in computational methods.
