Mapping the evolution of scientific fields

TL;DR

This paper introduces a network-based method to analyze the evolution of scientific fields by tracking communities of related concepts over time, providing insights into their development and interactions.

Contribution

The paper presents a novel network analysis approach using PACS codes to identify and track scientific communities over time, revealing their dynamics and evolution.

Findings

Identified communities correspond to known scientific fields.

Community age correlates with size and activity.

Method enables prediction of future scientific trends.

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.