Minimum required Qt 5.x
|Submitted: Jan 30 2006|
Updated: Aug 19 2014
Social Networks Visualizer (SocNetV) is a cross-platform, user-friendly tool for the analysis and visualization of Social Networks, built on C++ and Qt5.
It lets you construct networks (mathematical graphs) with a few clicks on a virtual canvas or load networks of various formats (GraphML, GraphViz, Adjacency, Pajek, UCINET, etc) and then modify, analyse and visualize them.
Furthermore, random networks (Erdos-Renyi, Watts-Strogatz, ring lattice, etc) and known social network datasets (i.e. Padgett's Florentine families) can be easily recreated. SocNetV also offers a built-in web crawler, allowing you to automatically create networks from links found in a given initial URL.
The application computes basic network properties, such as density, diameter, geodesics and distances (geodesic lengths), connectedness, eigenvector, etc. It also calculates advanced structural measures for social network analysis such as centrality and prestige indices (i.e. closeness centrality, betweeness centrality, information centrality, proximity and rank prestige), triad census, cliques, clustering coefficient, etc.
SocNetV offers various layout algorithms based either on prominence indices or dynamic models (i.e. Spring-embedder) for meaningful visualizations of social networks. There is also comprehensive documentation, both online and while running the application, which explains each feature and algorithm of SocNetV in detail.
The program is Free Software, licensed under the GNU General Public License 3 (GPL3). The documentation is also Free, licensed under the Free Documentation License (FDL).
Version 1.2 - Aug 2014
* Changed conceptualization of importance indices:
In general, all indices attempt to measure the visibility, the importance
or the "Prominence" of each node. But from now on, following Wasserman & Faust
and Knoke & Burt, we now distinguish two types of prominence:
Centrality and Prestige.
Most Centrality indices were designed for undirected graphs (symmetric),
where the relations are non-directional. They can also be calculated to
directed relations and digraphs by focusing on "choices made" (or outLinks).
For digraphs, where the relations are directional, we introduce a range of
Prestige indices which focus on "choices received". These indices
measure the nominations or ties to each node from all others (or inLinks).
Thus, Prestige indices can only be calculated on directed graphs, and measure
the status, rank or popularity of each node.
According to the new conceptualization, the "Centralities" menu has been
renamed to Centrality & Prestige. Centrality indices can be applied on both
graphs and digraphs (measuring outLinks) while Prestige indices can be
calculated only on digraphs and they measure inLinks.
* New Prestige indices: Degree Prestige, Proximity Prestige and PageRank Prestige.
* New "reachability" statistics: Walks (of given length), Total Walks
Matrix (for any path length up to g-1), and Reachability Matrix
* New Connectedness statistic: Checks whether the graph is connected, weakly
connected (digraph) or disconnected.
* New "distance" index: Eccentricity e, the maximum farness of the node from all others
* Revamped GUI. Toolbox now has two tabs: Controls and Statistics. In
Controls, all the essential features are available grouped in Edit (add
or remove node/link), Analyse (distances, connectivity, clusterability,
prominence indices) and Visualize (by prominence index or dynamic models)
boxes.Also renamed Statistics menu to Analysis
* New level visualization layouts: By IR Closeness Centrality, Stress Centrality,
Eccentricity Centrality, Power Centrality, Information Centrality,
Degree Prestige, Proximity Prestige and Pagerank Prestige
* New circular visualization layout: By Proximity Prestige
* New automagically recreated dataset:
* SocNetV Manual: Updated documentation (added new indices and corrected wording)
and added the Manual in Mac OS X .dmg package.
* Fixed Bugs: Closeness Centrality in disconnected graphs/digraphs (it did not
drop isolates), wrong classes for PC indices, Stress Centrality (wrong maxindex
and circular layout in digraphs), not displaying of edge weights,
Matrix::product errors, Eccentricity Centrality (wasn't reported as the inverse e),
Geodesic Distance (it reported two nodes as connected even if their distance was 0)
* Matrix Class: dded new operators in Matrix (+,*),
* Dropped Graph Eccentricity as it is known as Eccentricity Centrality