With respect to visualization, network analysis tools are used to change the layout, colors, size and other properties of the network representation. Visualization often also facilitates qualitative interpretation of network data. Visual representations of social networks are important to understand network data and convey the result of the analysis. 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. 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. For example, node-level features can include network phenomena such as betweenness and centrality, or individual attributes such as age, sex, or income. Network features can be at the level of individual nodes, dyads, triads, ties and/or edges, or the entire network. Networks can consist of direct linkages between nodes or indirect linkages based upon shared attributes, shared attendance at events, or common affiliations. 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. 3 Collection of social network analysis tools and libraries.
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