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All of the tools above contain visualization capabilities.

Net Miner, igraph, Cytoscape, mux Viz and Network X have the highest level of functionality in terms of producing high-quality graphics.

Interactive Data Visualization technology often includes social network analysis capabilities.

In general, the GUI packages are easier to learn, while scripting tools are more powerful and extensible.

Widely used and well-documented GUI packages include Net Miner, UCINet, Pajek (freeware), GUESS, ORA, Cytoscape, Gephi and mux Viz (opensource).

Private GUI packages directed at business customers include: Orgnet, which provides training on the use of its software, Polinode, Keyhubs, Key Lines, KXEN and Keynetiq.

Other SNA platforms, such as Idiro SNA Plus, have been specifically developed for particular industries such as telecoms and online gaming where massive data sets need to be analyzed.

Commonly used and well-documented scripting tools used for network analysis include: Net Miner with Python scripting engine, the statnet suite of packages for the R statistical programming language, igraph, which has packages for R and Python, mux Viz (based on R statistical programming language and GNU Octave) for the analysis and the visualization of multilayer networks, the Network X library for Python, and the SNAP package for large-scale network analysis in C++ and Python.

Though difficult to learn, some of these open source packages are growing much faster in terms of functionality and features than privately maintained software, and extensive documentation and tutorials are available.Visualization often also facilitates qualitative interpretation of network data.With respect to visualization, network analysis tools are used to change the layout, colors, size and other properties of the network representation.Social network analysis software (SNA software) is software which facilitates quantitative or qualitative analysis of social networks, by describing features of a network either through numerical or visual representation.project teams, classrooms, sports teams, legislatures, nation-states, disease vectors, membership on networking websites like Twitter or Facebook, or even the Internet.Networks can consist of direct linkages between nodes or indirect linkages based upon shared attributes, shared attendance at events, or common affiliations.

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