Forecasting Conceptual Diffusion in Science: The Case of Quantum Computing
Understanding and anticipating scientific change requires models that distinguish between endogenous consolidation and exogenous diffusion of scientific concepts. Using the quantum computing subtree of concepts in OpenAlex, we construct a temporally resolved concept co-occurrence network and track each concept pair through its upstream citation lineage and downstream diffusion. We train LightGBM models on distributional and diversity-aware features to predict four outcomes: endogenous reinforcement, exogenous diffusion, their ratio, and diffusion entropy. After controlling for overall publication growth of the scientific body, endogenous reinforcement proves largely unpredictable in the p...
| Authors | Thomas Maillart, Thibaut Chataing, David Dosu et al. |
|---|---|
| Primary category | cs.SI |
| Published | 2 June 2026 |
| Last updated at source | 2 June 2026 |
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