mlsanityData to 7 Oct 2026

Trajectories of Change: Approaches for Tracking Knowledge Evolution

arXiv 2501.00391 ↗First posted 31 Dec 2024cs.CL physics.hist-phcited by 1

Not on the map. Why?

Abstract (arXiv)

We explore local vs. global evolution of knowledge systems through the framework of socio-epistemic networks (SEN), applying two complementary methods to a corpus of scientific texts. The framework comprises three interconnected layers-social, semiotic (material), and semantic-proposing a multilayered approach to understanding structural developments of knowledge. To analyse diachronic changes on the semantic layer, we first use information-theoretic measures based on relative entropy to detect semantic shifts, assess their significance, and identify key driving features. Second, variations in document embedding densities reveal changes in semantic neighbourhoods, tracking how concentration of similar documents increase, remain stable, or disperse. This enables us to trace document trajectories based on content (topics) or metadata (authorship, institution). Case studies of Joseph Silk and Hans-J"urgen Treder illustrate how individual scholar's work aligns with broader disciplinary shifts in general relativity and gravitation research, demonstrating the applications, limitations, and further potential of this approach.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 10 of its 62 references that are in the map. First posted on arXiv 31 Dec 2024.

Builds on

10 of 62 references.

References · 10

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  2. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  3. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  4. 2018Deep contextualized word representationscited by 2,285
  5. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,404
  6. 2022BERTopic: Neural topic modeling with a class-based TF-IDF procedurecited by 779
  7. 2020Analysing Lexical Semantic Change with Contextualised Word Representationscited by 92
  8. 2014Statistically Significant Detection of Linguistic Changecited by 82
  9. 2017Individuals, Institutions, and Innovation in the Debates of the French Revolutioncited by 10
  10. 2024Tracing the Development of the Virtual Particle Concept Using Semantic Change Detectioncited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.