  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.
