networkdata

The package contains a large variety of different network datasets (all in igraph format). So far, it includes datsets from the following repositories:

• Freeman’s datasets from http://moreno.ss.uci.edu/data
• Movie networks from https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/T4HBA3
• Covert networks from https://sites.google.com/site/ucinetsoftware/datasets/covert-networks
• Animal networks from https://bansallab.github.io/asnr/
• Shakespeare’s plays networks build with data from https://github.com/mallaham/Shakespeare-Plays
• Some networks from http://konect.uni-koblenz.de/
• Tennis networks compiled from https://github.com/JeffSackmann (please give credit to him if you use this data)
• Star Wars Character Interactions (Episode 1-7) from https://github.com/evelinag/StarWars-social-network

The package includes 980 datasets containing 2135 networks.

A list of all datasets can be obtained with

data(package = "networkdata")

Alternatively, use the function show_networks() to get a list of datasets with desired properties. removed

Feel free to add your own dataset via a pull request

Installation

Due to the nature of the package (only data, no functions), the package will not go to CRAN at any point. However, the package is available via drat (If you are looking for stable builds of the package). With drat, you can install and upgrade non-CRAN packages directly from R using the standard install.packages() and update.packages() functions.

# install.packages("drat")
drat::addRepo("schochastics")
install.packages("networkdata")

The developer version can be installed with:

#install.packages("remotes")
remotes::install_github("schochastics/networkdata")

The required space for the package is ~22MB, given that it includes a lot of data.

Notes

• Please report any missing sources/references for datasets.
• Many datasets were automatically assembled and may thus contain errors (not all were manually checked). If you spot any, please report them. Check the original sources for any inconsistencies if you want to use the data in an academic paper.