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| Social Network Visualizer v2.8
Social Network Visualizer v2.8 Social Network Visualizer (SocNetV) is a cross-platform, user-friendly software for social network analysis and visualization. Social Networks are displayed and analyzed as mathematical graphs, where vertices depict actors/agents and edges represent their relations. With SocNetV you can draw social networks with a few clicks on a virtual canvas or load field data from various social network formats supported such as GraphML, GraphViz, Adjacency, Pajek, UCINET, etc. Furthermore, you can create random networks using various random network generation models (Barabási–Albert Scale-Free, Erdős–Rényi, Watts-Strogatz Small-World, d-regular, ring lattice, etc) or recreate famous social network analysis datasets, i.e. Padgett's Florentine families. A simple web crawler is also included to automatically create "social networks" from links found in a given initial URL. The crawler scans the given web page for links and visualizes the network of all webpages/sites linked from it. SocNetV enables you to edit your social network data through point-and-click, analyse their social and mathematical properties, produce reports for these properties and embed visualization layouts for relevant presentation of each network. It also supports multirelational loading and editing. You can load a social network consisting of multiple relations or create a social network on your own and add multiple relations to it. SocNetV easily computes basic graph-theoretic properties, such as density, diameter, geodesics and distances (geodesic lengths), connectedness, eccentricity, etc. But it also computes advanced structural measures for social network analysis such as centrality and prestige indices (i.e. closeness centrality, betweeness centrality, information centrality, power centrality, proximity and pagerank prestige), triad census, clique census, clustering coefficient, etc. The application supports various layout algorithms based either on prominence indices (i.e. circular, level and nodal sizes by centrality score) or on force-directed models (i.e. Eades Spring Embedder, Fruchterman-Reingold, etc) for meaningful visualizations of the social networks. The program is Free Software, licensed under the GNU General Public License ...
|3,175||May 28, 2021
Dimitris V. Kalamaras
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