Mapping the Evolution of Scientific Fields

TLDR

Scientific fields interact cross‑disciplinarily, yet a formal description of their evolution is lacking. The authors propose a network‑based approach to study and predict the evolution of scientific fields. They construct an idea network of PACS numbers linked by co‑citation, detect communities to define fields, and track their evolution from 1985 to 2006. Identified communities correspond to known fields, with older fields being larger and more active.

Abstract

Despite the apparent cross-disciplinary interactions among scientific fields, a formal description of their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time evolution of these fields over the course of 1985–2006. The communities we identify map to known scientific fields, and their age depends on their size and activity. We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.