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Backbone: An R package for extracting the backbone of bipartite projections

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  • Rachel Domagalski
  • Zachary P Neal
  • Bruce Sagan

Abstract

Bipartite projections are used in a wide range of network contexts including politics (bill co-sponsorship), genetics (gene co-expression), economics (executive board co-membership), and innovation (patent co-authorship). However, because bipartite projections are always weighted graphs, which are inherently challenging to analyze and visualize, it is often useful to examine the ‘backbone,’ an unweighted subgraph containing only the most significant edges. In this paper, we introduce the R package backbone for extracting the backbone of weighted bipartite projections, and use bill sponsorship data from the 114th session of the United States Senate to demonstrate its functionality.

Suggested Citation

  • Rachel Domagalski & Zachary P Neal & Bruce Sagan, 2021. "Backbone: An R package for extracting the backbone of bipartite projections," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-20, January.
    • Handle: RePEc:plo:pone00:0244363
    DOI: 10.1371/journal.pone.0244363
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    References listed on IDEAS

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    1. Zhang Bin & Horvath Steve, 2005. "A General Framework for Weighted Gene Co-Expression Network Analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 4(1), pages 1-45, August.
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    1. van Meeteren, Michiel & Trincado-Munoz, Francisco & Rubin, Tzameret H. & Vorley, Tim, 2022. "Rethinking the digital transformation in knowledge-intensive services: A technology space analysis," Technological Forecasting and Social Change, Elsevier, vol. 179(C).

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