Conceptual structure and the growth of scientific knowledge

TL;DR

This study empirically analyzes how the structure of scientific concepts influences knowledge growth, revealing that more innovative work occurs with dynamic core structures, and consensus correlates with stability in conceptual organization.

Contribution

It provides large-scale empirical evidence linking the evolution of conceptual structures to scientific progress across physical and social sciences.

Findings

More innovative work occurs with higher conceptual churn.

Larger cores are associated with increased scientific innovation.

Scientific consensus correlates with reduced conceptual churn.

Abstract

How does scientific knowledge grow? This question has occupied a central place in the philosophy of science, stimulating heated debates, but yielding no clear consensus. Many explanations can be understood in terms of whether and how they view the expansion of knowledge as proceeding through the accretion of scientific concepts into larger conceptual structures. Here, we examine these views empirically, performing a large-scale analysis of the physical and social sciences, spanning five decades. Using natural language processing techniques, we create semantic networks of concepts, wherein noun phrases become linked when used in the same paper abstract. For both the physical and social sciences, we observe increasingly rigid conceptual cores (i.e., densely connected sets of highly central nodes) accompanied by the proliferation of periphery concepts (i.e., sparsely connected nodes that are highly connected to the core). Subsequently, we examine the relationship between conceptual structure and the growth of scientific knowledge, finding that scientific works are more innovative in fields with cores that have higher conceptual churn and with larger cores. Furthermore, scientific consensus is associated with reduced conceptual churn and fewer conceptual cores. Overall, our findings suggest that while the organization of scientific concepts is important for the growth of knowledge, the mechanisms vary across time.