Tracing the Evolution of Physics on the Backbone of Citation Networks

TL;DR

This paper develops a method to trace the evolution of scientific ideas by constructing a citation-based backbone tree, revealing hierarchical structures and improving classification of research fields.

Contribution

It introduces a novel approach to identify the most important citation links, forming a backbone that captures the genealogy of scientific research.

Findings

Citation backbones reflect hierarchical and fractal structures.

Backbones enable accurate classification of scientific fields.

The method outperforms traditional spanning trees in capturing research evolution.

Abstract

Many innovations are inspired by past ideas in a non-trivial way. Tracing these origins and identifying scientific branches is crucial for research inspirations. In this paper, we use citation relations to identify the descendant chart, i.e. the family tree of research papers. Unlike other spanning trees which focus on cost or distance minimization, we make use of the nature of citations and identify the most important parent for each publication, leading to a tree-like backbone of the citation network. Measures are introduced to validate the backbone as the descendant chart. We show that citation backbones can well characterize the hierarchical and fractal structure of scientific development, and lead to accurate classification of fields and sub-fields.