Abstract
The backbone package for R implements models for extracting the backbone – a sparse unweighted network containing only the most ‘important’ edges – from a weighted or unweighted network, where different models adopt different perspectives on what makes an edge important. The use of network backbones simplifies analysis and visualization when the original network is weighted or dense. This paper introduces and demonstrates the use of the backbone package for R to extract network backbones. After providing an overview of backbone’s workflow and structure, I describe several backbone extraction models, illustrating backbone extraction in a series of toy examples. I then present a complete empirical case study using bill sponsorship data from the 108th U.S. Senate. I conclude with some recommendations for backbone extraction, and an agenda for planned extensions to backbone.
Cite
CITATION STYLE
Neal, Z. P. (2026). Backbone 3.0: An R package for extracting network backbones. PLOS ONE, 21(5 May). https://doi.org/10.1371/journal.pone.0349258
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.