A Semantic Geometry for Uncovering Paradigm Dynamics via Scientific Publications

2026-04-16

AI Summary

This study addresses the need to quantify semantic relationships between knowledge foundations and diffusion in scientific publications, thereby uncovering the dynamic mechanisms underlying shifts in scientific paradigms. Building on the Reference–Focal Publication–Citation (R-P-C) triadic structure, the authors propose a semantic geometric model that integrates natural language processing, semantic embeddings, and network analysis to characterize the semantic positioning of publications within knowledge transmission and dissemination. For the first time, this framework directly links paradigm dynamics with semantic structure, identifying three distinct research archetypes: consolidating, exploring, and balanced. It elucidates how exploratory studies suffer from slow diffusion due to semantic discontinuities, whereas consolidating studies gain rapid recognition. The work also reveals how team size influences research type and citation trajectories, offering a novel tool for monitoring evolving scientific paradigms.

Technology Category

• Game Theory and Economic Paradigms: Other Foundations of Game Theory & Economic Paradigms
• Data Mining & Knowledge Management: Semantic Web
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Web Mining and Content Analysis: Models for Web evolution
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs

Abstract

Science advances not only by accumulating discovered patterns but by changing how new problems and solutions are expressed. While structural indicators track scholarly attention, they offer only an indirect proxy for the reorganization of meaning. We propose a semantic geometry based on the R-P-C (references, focal publication, and citing publications) framework to quantify how a publication positions itself relative to its knowledge base and diffusion. This geometry identifies three publication types: consolidating, exploratory and balanced. Our results show that the semantic similarity and distance between a publication's knowledge base and diffusion serve as a mechanistic explanation for disruption, with novelty (atypical reference combinations) acting as an antecedent disturbance that triggers a semantic rupture. This is related to team size, where small teams preserve a higher potential for exploratory departures while large collaborations systematically align with paradigmatic consolidation. Crucially, this geometry explains why citation trajectories differ; consolidating research earns rapid recognition by lowering comprehension costs, while exploratory work faces high paradigm conversion costs that result in slower, more selective diffusion. Collectively, this R-P-C framework provides a robust instrument for monitoring the dynamic of scientific paradigms.

Problem

• semantic geometry
• paradigm dynamics
• scientific publications
• disruption
• knowledge reorganization

Innovation

• semantic geometry
• paradigm dynamics
• scientific disruption
• R-P-C framework
• exploratory vs consolidating research