Fields of Interest

The Digital Methods in the Humanities and Social Sciences team is by nature interdisciplinary, positioned at the intersection of the humanities and social sciences (HSS) and computer science. It focuses on two main axes:

The development and application of computational methods to address questions in the humanities and social sciences;
The study of societal practices and digital uses through qualitative and quantitative methods from the human and social sciences.

The team draws on technologies such as artificial intelligence, data science, knowledge extraction, and natural language processing, while also using research techniques from sociology, history, and other disciplines. This dual expertise allows the team to contribute to both the advancement of HSS and the evolution of computational tools through concrete and diversified case studies.

Digital technology as a method. The team applies computer science methodologies - such as machine learning, data mining, and natural language processing - to analyze and visualize data traditionally used in the humanities and social sciences (e.g. textual archives, historical documents, qualitative or quantitative corpora). This not only generates new insights in HSS but also encourages methodological innovation by challenging existing tools in varied research contexts.

Digital technology as an object of study. Beyond methodological applications, the team also investigates how digital technologies shape contemporary practices. Drawing on fieldwork methods (surveys, interviews, observations), the team explores issues such as political extremism, youth cultural practices, and the behavioural impacts of online gambling.

The team brings together researchers from the humanities, social sciences, and computer science who collaborate on interdisciplinary projects combining digital humanities, knowledge extraction, and the analysis of social practices.

Their work focuses on the following research themes:

History of political ideas
History of books and media
Sociology of play, leisure, and cultural practices
Sociology of behavioral addictions and mental health
Sociology of deviance, crime, and imprisonment
Sociology of education and informal learning
Digital humanities
Data mining, text mining, and data visualization
Knowledge-intensive processes

Methodological Contributions

In connection with these themes, the team also develops digital methods specifically adapted to the types of data under study, while ensuring their general relevance for a wide range of HSS disciplines. These include:

Knowledge extraction from historical documents
Development of generic methods for digital history
Analysis and visualization of online gambling practices

Applications

Building on this interdisciplinary foundation, the DMHSS team actively contributes to the design and deployment of digital tools that address both academic and societal challenges. Its projects offer valuable resources for researchers in computer science—by grounding algorithmic development in real-world data—and generate outputs that support humanities and social science research, education, and public engagement.

Examples of current applications include:

Processing of digitised historical documents: methods for text extraction, semantic enrichment, and structured annotation tailored to the needs of historians and archivists.
Detection and prevention of gambling-related addiction: analysis of behavioural data and deployment of survey instruments to better understand and mitigate problematic uses.

These applications are developed in close collaboration with other LRE teams, such as the Image Processing and Pattern Recognition team and the AI team, as well as with various partners outside EPITA, including cultural institutions, research centres, and public stakeholders.