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This guide defines network analysis and discusses several network analysis tools and methods

**Packages in R **

- ggraph plots network graphs using the conventions and power of ggplot2
- igraph is a collection of network analysis tools with the emphasis on efficiency, portability, and ease of use. igraph is open source and free, and can be used in R, Python, and C++
- network manages relational data in R. Networks can be created with any combination of undirected/directed, valued/unvalued, dyadic/hyper, and single/multiple edges
- networkD3 creates D3 JavaScript network, tree, dendrogram, aand Sankey graphs
- tidygraph conceptualizes a network graph as two tidy data frames consisting of node and edge data
- Resources
- Alex Brey, Temporal Network Analysis with R
- Ryan Deschamps, Correspondence Analysis for Historical Research with R
- Katherine Ognyanova, Network Analysis and Visualization with R and igraph
- Jesse Sadler, Introduction to Network Analysis with R: Creating Static and Interactive Network Graphs

**Networkx**. Networkx is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

- NetworkX documentation
- NetworkX tutorial
- Resources
- Aric Hagberg, Dan Schult, and Pieter Swart, Networkx Tutorial
- Coursera, Applied Social Network Analysis in Python
- DataCamp, Graph Optimization with Networkx in Python

- Last Updated: Jan 31, 2024 11:10 AM
- URL: https://infoguides.gmu.edu/networkanalysis
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