Social network analysis software Collection of social network analysis tools and libraries Collection of social network analysis tools and libraries

| Product | Main_Functionality | Input_Format | Output_Format | Platform | License_and_cost | Notes_ |
|---|---|---|---|---|---|---|
| NetworkX | Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. | GML, Graph6/Sparse6, GraphML, GraphViz (.dot), NetworkX (.yaml, adjacency lists, and edge lists), Pajek (.net), LEDA | GML, Gnome Dia, Graph6/Sparse6, GraphML, GraphViz (.dot), NetworkX (.yaml, adjacency lists, and edge lists), Pajek (.net), LEDA, and assorted image formats (.jpg, .png, .ps, .svg, et al.) | Open source (GPL and similar) | Free | NetworkX (NX) is a toolset for graph creation, manipulation, analysis, and visualization. User interface is through scripting/command-line provided by Python. NX includes a several algorithms, metrics and graph generators. Visualization is provided through pylab and graphviz. , NX is an open-source project, in active development since 2004 with an open bug-tracking site, and user forums. Development is sponsored by Los Alamos National Lab. |
| R | Social network analysis within the versatile and popular R environment | R will read in almost any format data file | R has write capability for most data formats | Windows, Linux, Mac | Open source | R contains several packages relevant for social network analysis: igraph is a generic network analysis package; sna performs sociometric analysis of networks; network manipulates and displays network objects; tnet performs analysis of weighted networks, two-mode networks, and longitudinal networks; ergm is a set of tools to analyze and simulate networks based on exponential random graph models exponential random graph models; Bergm provides tools for Bayesian analysis for exponential random graph models, hergm implements hierarchical exponential random graph models; `RSiena` allows the analyses of the evolution of social networks using dynamic actor-oriented models; latentnet has functions for network latent position and cluster models; degreenet provides tools for statistical modeling of network degree distributions; and networksis provides tools for simulating bipartite networks with fixed marginals. |