InterIDEAS: Philosophical Intertextuality via LLMs

The formation and circulation of ideas in philosophy have profound implications for understanding philosophical dynamism-enabling us to identify seminal texts, delineate intellectual traditions, and track changing conventions in the act of philosophizing. However, traditional analyses of these issues often depend on manual reading and subjective interpretation, constrained by human cognitive limits. We introduce InterIDEAS, a pioneering dataset designed to bridge philosophy, literary studies, and natural language processing (NLP). By merging theories of intertextuality from literary studies with bibliometric techniques and recent LLMs, InterIDEAS facilitates both quantitative and qualitative analysis of the intellectual, social, and historical relations in authentic philosophical texts. This dataset not only assists the study of philosophy but also contributes to the development of language models by providing a training corpus that enhances their interpretative capacity. The code URL for the dataset is https://github.com/ interIDEAS/InterIDEAS_data .