Overview
Networks can consist of anything from families, project teams, classrooms, sports teams, legislatures, nation-states, disease vectors, membership on networking websites like Twitter or Facebook, or even the Internet. Network features can be at the level of individual nodes, dyads, triads, ties and/or edges, or the entire network. For example, node-level features can include network phenomena such as betweeness and centrality, or individual attributes such as age, sex, or income. SNA software generates these features from raw network data formatted in an edgelist, adjacency list, or adjacency matrix (also called sociomatrix), often combined with (individual/node-level) attribute data. Though the majority of network analysis software uses a plain text ASCII data format, some software packages contain the capability to utilize relational databases to import and/or store network features.
Some SNA software can perform predictive analysis. This includes using network phenomena such as a tie to predict individual level outcomes (often called peer influence or contagion modeling), using individual-level phenomena to predict network outcomes such as the formation of a tie/edge (often called homophily models) or particular type of triad, or using network phenomena to predict other network phenomena, such as using a triad formation at time 0 to predict tie formation at time 1.
Network analysis software generally consists of either packages based on graphical user interfaces (GUIs), or packages built for scripting/programming languages. GUI packages are easier to learn, while scripting tools are more powerful and extensible. Widely used and well-documented GUI packages include NetMiner, UCINet, Pajek (freeware), GUESS, ORA, and Cytoscape. Private GUI packages directed at business customers include: Orgnet, which provides training on the use of its software, Keyhubs, and KXEN. 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: NetMiner with Python scripting engine, the statnet suite of packages for the R statistical programming language, igraph, which has packages for R and Python, the NetworkX library for Python, and the SNAP package for large-scale network analysis in C++. Though difficult to learn, 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. They also come free thanks to open-source licensing.
Visual representations of social networks are important to understand network data and convey the result of the analysis. 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. All of the tools above contain visualization capabilities, NetMiner, igraph, Cytoscape, NetworkX have the highest level of functionality in terms of producing high-quality graphics.
Interactive Data Visualization technology often includes social network analysis capabilities. In this technology, other forms of data visualization are used to interact with social network graphs. These forms of visualization include a variety of charting visualizations, tables, time lines and maps. Users have the ability to display data in any of these forms while also applying functions to explore the data in a highly interactive user experience. For example, complex social network graphs can be filtered using summary chart visualizations or time lines to isolate portions of the social network graph that are of interest to the analyst. Interactive Data Visualization may also include the ability to integrate data and publish dashboards or templates to report results.
Also worthy of mention are the variety of tools built primarily for network visualization, some of which also contain analytic features. These include general purpose visualization tools such as SocNetV and Tulip; tools designed for medical applications such as SocioMetrica; tools designed for law-enforcement and intelligence organizations such as i2 Analyst's Notebook, SilentRunner Sentinel, and Sentinel Visualizer; tools designed for corporations and businesses such as NodeXL, RapidNet, Keyhubs, Idro, Ipoint, and Sonamine.
Read more about this topic: Social Network Analysis Software