Tracing the evolution of physics with a keyword co-occurrence network

Abstract

Describing the evolution of science is a salient work not only for revealing the scientific trend but also for establishing a scientific classification system. In this paper, we investigate the evolution of science by observing the structure of and the change on keyword co-occurrence networks. Starting from seven target physics fields and their initial keywords selected by experts from the Korean Physical Society, we generate keyword co-occurrence networks to capture better topological structure with our proposed approach. In this way, we can construct a more relevant and abundant keyword network from a small set of initial keywords. With these networks, we successfully identify the scientific sub-field by detecting communities and extracting core keywords of each community. Furthermore, we use a time-snapshot keyword network to trace the temporal evolution of sub-fields, and the resultant temporal change of the community membership explains the evolution of the research field well. Our approach for tracing the evolution of a research field with a keyword co-occurrence network can shed light on identifying and assessing the evolution of science.