Objective
Large collections of literary texts contain invaluable knowledge for understanding narratives, the evolution of literary genres, and, more broadly, the development of human culture. However, no method currently exists that can fully unlock the depth of insight contained in these corpora. While human analysis struggles to scale, automated approaches often remain superficial, failing to grasp the structure of narratives or accurately reflect their complexity. Narratology—the study of narrative forms and functions—thus remains a particularly challenging domain where computational tools cannot replace human expertise and interpretation. The goal of our project is to develop a novel approach that combines the strengths of distant and close reading, enabling narratological analysis at scale. Our method builds on new natural language processing (NLP) techniques designed specifically for large fictional corpora, yielding representations that retain textual complexity and support human interpretation. These models will be informed by concepts from narratology and literary theory, two areas largely overlooked in existing NLP research. We will first apply this methodology to large French literary corpora (which, for example, account for 40% of published novels in the 19th century) that have not yet been studied in depth and for which no appropriate computational tools currently exist. We will then explore how similar techniques can be applied to Russian literary corpora, with a particular focus on tracing the influence of French literature—especially the international role played by women authors—on the formation of modern Russian fiction. This comparative approach will help demonstrate the adaptability of our method to new languages, and its relevance for cross-cultural studies in narratology. Ultimately, the project aims to transform literary analysis and open new pathways for understanding cultural evolution through large, previously underexplored collections of novels.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2025-ADG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
75794 Paris
France
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.