The R Journal: article published in 2017, volume 9:1

Network Visualization with ggplot2
Sam Tyner, François Briatte and Heike Hofmann , The R Journal (2017) 9:1, pages 27-59.

Abstract This paper explores three different approaches to visualize networks by building on the grammar of graphics framework implemented in the ggplot2 package. The goal of each approach is to provide the user with the ability to apply the flexibility of ggplot2 to the visualization of network data, including through the mapping of network attributes to specific plot aesthetics. By incorporating networks in the ggplot2 framework, these approaches (1) allow users to enhance networks with additional information on edges and nodes, (2) give access to the strengths of ggplot2, such as layers and facets, and (3) convert network data objects to the more familiar data frames.

Received: 2015-11-14; online 2017-05-10
CRAN packages: igraph, sna, network, statnet, ggplot2, ggnetwork, geomnet, ggmap, ggfortify, GGally, gcookbook, intergraph, grid, ggrepel, ndtv, gridExtra, tnet, ggCompNet, tidyverse, plyr, dplyr
CRAN Task Views implied by cited CRAN packages: gR, SocialSciences, Graphics, Optimization, Spatial, Bayesian, Phylogenetics, WebTechnologies
Bioconductor packages: ggbio, ggtree

This article is licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2017-023,
  author = {Sam Tyner and François Briatte and Heike Hofmann},
  title = {{Network Visualization with ggplot2}},
  year = {2017},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2017-023},
  url = {https://doi.org/10.32614/RJ-2017-023},
  pages = {27--59},
  volume = {9},
  number = {1}
}