Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.17594 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866912972656345088 |
|---|---|
| author | Aguilar-Valdez, Sofía Degaetano-Ortlieb, Stefania |
| author_facet | Aguilar-Valdez, Sofía Degaetano-Ortlieb, Stefania |
| contents | While context embeddings produced by LLMs can be used to estimate conceptual change, these representations are often not interpretable nor time-aware. Moreover, bias augmentation in historical data poses a non-trivial risk to researchers in the Digital Humanities. Hence, to model reliable concept trajectories in evolving scholarship, in this work we develop a framework that represents prototypical concepts through complex networks based on topics. Utilizing the Royal Society Corpus, we analyzed two competing theories from the Chemical Revolution (phlogiston vs. oxygen) as a case study to show that onomasiological change is linked to higher entropy and topological density, indicating increased diversity of ideas and connectivity effort. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_17594 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Modeling Changing Scientific Concepts with Complex Networks: A Case Study on the Chemical Revolution Aguilar-Valdez, Sofía Degaetano-Ortlieb, Stefania Physics and Society Computation and Language I.2.7; J.4; J.5 While context embeddings produced by LLMs can be used to estimate conceptual change, these representations are often not interpretable nor time-aware. Moreover, bias augmentation in historical data poses a non-trivial risk to researchers in the Digital Humanities. Hence, to model reliable concept trajectories in evolving scholarship, in this work we develop a framework that represents prototypical concepts through complex networks based on topics. Utilizing the Royal Society Corpus, we analyzed two competing theories from the Chemical Revolution (phlogiston vs. oxygen) as a case study to show that onomasiological change is linked to higher entropy and topological density, indicating increased diversity of ideas and connectivity effort. |
| title | Modeling Changing Scientific Concepts with Complex Networks: A Case Study on the Chemical Revolution |
| topic | Physics and Society Computation and Language I.2.7; J.4; J.5 |
| url | https://arxiv.org/abs/2603.17594 |