Building a list specifically dedicated to network analysis presents the opportunity to cite more R packages that focus on that task, such as the rapidly expanding list of packages to estimate exponential random graph models with R.
The list is intended to join the list of awesome lists that abide to the content and stylistic guidelines of the awesome manifesto. It currently features over a hundred links, a quarter of which are links to R packages.
It is perhaps unsurprising that R has become so crucially important for network analysis:
- R is at the centre of many efforts to build statistical models for network data: the Statnet project uses R packages, and SIENA switched from being a Windows program to becoming an R package in 2011.
- Last, but perhaps most importantly from a development perspective, R packages are intended to be built and released as free and open source software that can be extended, improved, or simply read and understood by anyone.
The incredible amount of books, courses and tutorials on how to analyze networks with R is also contributing to that trend, and building the awesome list on network analysis is helping me to organize my many bookmarks on the topic.
Some of the R packages cited in the list could also feed into a CRAN Task View on network analysis, which is something I might come back to.
More ideas on how to document the universe of R (and Python) packages for network analysis are currently being discussed on the SOCNET mailing-list, where subscribers have circulated publicly editable Google Spreadsheets to that effect.
: as of version 1.0, the list contains over 200 awesome items, organised into ten sections that cover books, conferences, courses, datasets, journals, professional groups, review articles, software, tutorials and miscellaneous stuff. Enjoy!
- First published on April 11th, 2016