backbone: An R package to extract network backbones

TL;DR

The paper introduces the 'backbone' R package for extracting simplified, important edges from complex networks, aiding analysis across various domains with practical examples and discussion of statistical inference issues.

Contribution

It presents a comprehensive R package implementing backbone extraction methods for different network types, with reproducible examples and insights into statistical inference challenges.

Findings

Effective extraction of network backbones demonstrated on real-world data

Discussion of statistical inference issues in backbone extraction

Application examples across transportation, political, and social networks

Abstract

Networks are useful for representing phenomena in a broad range of domains. Although their ability to represent complexity can be a virtue, it is sometimes useful to focus on a simplified network that contains only the most important edges: the backbone. This paper introduces and demonstrates the `backbone' package for R, which implements methods for extracting the backbone from weighted networks, weighted bipartite projections, and unweighted networks. For each type of network, fully replicable code is presented first for small toy examples, then for complete empirical examples using transportation, political, and social networks. The paper also demonstrates the implications of several issues of statistical inference that arise in backbone extraction. It concludes by briefly reviewing existing applications of backbone extraction using the `backbone' package, and future directions for research on network backbone extraction.