SOURCE-LINKED INTELLIGENCE

Graphs and Ontologies for Literary Evolution Models

CORDIS · observation · Publication date unknown

nse – which will be used to test hypotheses related to the accumulation of cultural traits in stories and their effectiveness in achieving cognitive and emotional effects on readers. State-of-the-art machine learning algorithms and advanced statistical modelling tools will be employed to create a major breakthrough in computational literary studies, possibly also contributing to the revision of cultural evolution theories. By focusing on the relations between stories in five different languages, collected from countries in all continents, GOLEM will provide an unprecedented insight into how storytelling, one of the most ancient cultural systems, evolves. Literary history and criticism have offered refined accounts of how fiction works, mostly relying on case studies of limited extent. It is now time to provide robust statistical evidence of the anthropological function of fiction and of how it adapts to different circumstances and cultures, empowering readers to cope with their cultural or societal contexts. computational literary studies; reader response; cultural evolution

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recordType

award

status

SIGNED

region

EU

value

1194088.75

unit

EUR