Distinguishing gradual change from the emergence of genuinely new directions is a central challenge in tracking how research fields evolve. This preprint explores local versus global evolution of knowledge systems through the socio-epistemic networks (SEN) framework, pairing an information-theoretic measure of semantic shift with density estimation over text embeddings to detect and characterize change in a corpus of scientific texts.
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- Authors: Raphael Schlattmann and Malte Vogl
- Preprint: arXiv:2501.00391
- Featured image: figure from the preprint
