Conceptual structure and the growth of scientific knowledge

How does scientific knowledge grow? For generations, this question has occupied a central place in the philosophy of science, stimulating heated debates, but yielding no clear consensus. Many proposed 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 techniques from natural language processing, we create semantic networks of concepts, wherein single- and multi-word noun phrases become linked when they are 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). In the physical sciences, these changes coincide with an increasing number of cores, while in the social sciences, the number of cores is decreasing. In subsequent analyses, 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, with larger cores, and an overall smaller number of cores, the latter of which is also associated with more scientific consensus. Overall, our findings suggest that while the organization of scientific concepts is important for the growth of knowledge, the mechanisms vary across fields and time.