Analysis and visualization of Social Networks

Social Networks Visualizer

Social Networks Visualizer (SocNetV) is a social network analysis and visualization tool. You can draw a network (graph) or load an existing one (GraphML, UCINET, Pajek, etc), compute statistics, centralities, and apply various layout algorithms based on centrality or prestige indices (i.e. Betweeness) or on dynamic models (i.e. spring-embedder).

With SocNetV you can:

  • Draw social networks with a few clicks on a virtual canvas, load field data from a file in a supported format (GraphML, GraphViz, Adjacency, EdgeList, GML, Pajek, UCINET, etc) or crawl the internet to create a social network of connected webpages.
  • Edit actors and ties through point-and-click, analyse graph and social network properties, produce beautiful HTML reports and embed visualization layouts to the network.

SocNetV main features:

  • Standard graph and network cohesion metrics, such as density, diameter, geodesics and distances, connectedness, eccentricity, clustering coefficient, reciprocity, etc.
  • Matrix routines: Adjacency plot, Laplacian matrix, Degree matrix, Cocitation, etc
  • Advanced measures for social network analysis such as centrality and prestige indices (i.e. eigenvector and closeness centrality, betweenness centrality, information centrality, power centrality, proximity and pagerank prestige).
  • Fast algorithms for community detection, such as triad census, clique census,etc.
  • Structural equivalence analysis, using hierarchical clustering, actor similarities and tie profile dissimilarities, Pearson coefficients.
  • Layout models based either on prominence indices (i.e. circular, level and nodal sizes by centrality score) or on force-directed placement (i.e. Kamada-Kawai, Fruchterman-Reingold, etc) for meaningful visualizations of the social networks.
  • Multirelational network loading and editing. Load a social network consisting of multiple relations or create a social network on your own and add multiple relations to it.
  • Random network creation using various random network generation models (Barabási–Albert Scale-Free, Erdős–Rényi, Watts-Strogatz Small-World, d-regular, ring lattice, etc)
  • Famous social network analysis datasets, i.e. Padgett's Florentine families.
  • Built-in web crawler  to automatically create "social networks" from links found in a given initial URL. 
  • Comprehensive documentation, both online and inside the application, which explains each feature and algorithm of SocNetV in detail.