Minimum required Qt 5.x
|Submitted: Jan 30 2006|
Updated: Oct 10 2014
Social Networks Visualizer (SocNetV) is a cross-platform, user-friendly tool for the analysis and visualization of Social Networks, built in C++ and Qt.
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). Also, SocNetV enables you to modify the social networks, analyse their social and mathematical properties and apply visualization layouts for relevant presentation.
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 graph properties, such as density, diameter, geodesics and distances (geodesic lengths), connectedness, eccentricity, 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, power 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.
Source code, packages and executables for Windows, Linux and Mac OS X are available.
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 1.5 - Oct 10, 2014
* New feature: Prominence indices on valued networks
A new SSSP-solver algorithm has been implemented (Dijkstra)
which allows SocNetV to compute prominence indices on weighted
networks. When the graph edges are weighted, the application
asks the user if it should consider weights in computations.
Also, it asks the user if weights should be inverted or not.
This question is crucial since edge weights can have
different meanings. For instance they can denote cost or votes.
If they denote cost, then the geodesics should be those paths
with minimum value. But, if the weights denote votes, then the
geodesics could be those path with maximum value. In the latter
case, the user should choose to invert weights so that Dijkstra
compute the desired paths and distances.
* New feature: Standardized Centrality and Prestige scores
From this version all actor prominence indices report standardized
scores (from 0.0 to 1.0) where applicable. If there is no known
formula to compute such a standardized score for actors, then
SocNetV computes a std score by dividing the original index score
by the sum of index scores of all actors. For instance, this happens
on PRP. Warning: If the original prominence index has range
from 0 to 1 (i.e. EC and IRCC), SocNetV considers that as std and
does not compute anything else.
* Change: Prominence layouts are relative to highest score
From now on, all (circular, level and nodal size) visualization
layouts based on prominence scores are graphed relative to the highest
score in the network, instead to the theoretical max (1.0). For
instance in a circular layout, say the actor with the highest CC
has score 0.8. That node will appear to the center of the circular
layout. All other actors will appear on circles of radius relative
to that highest score. I.e. an actor with score 0.4 will appear on
a circle of radius 50% further from the screen center, while another
actor with CC score 0.2 will appear on a circle of radius 75% further
from the actor with the highest score.
* New feature: Work without isolates, if you like
The user can omit isolates and compute prominence indices
for the resulting graph.
* New feature: Graph connectedness
SocNetV can report the network connectedness (whether it is a
connected graph or digraph, unilateral etc). Also it can check
whether isolates exist that can be removed so that the graph
can become connected
* New feature: CC drops isolates by default
Up to v1.5, SocNetV did not compute CC scores if the network had
isolate nodes, instead it urged the user to use IRCC. From this
version, SocNetV checks if isolates exists and automatically drops
them in order to compute CC scores.
#1358678 Fix GDC calculation in weighted networks
#379558 Force-Directed algorithms produce poor layouts
#1365028 Methods isOutLinked & setOutLinked do not consider relations
#1365504 centralityInformation() should symmetrize adjacency matrix
#1366625 click on an edge does not select the right edge
#1369171 Group IC calculation yields incorrect results
#1371208 wrong power centrality scores
#1364955 vertices() should report only enabled vertices
#1369336 pagerank prestige reports wrong scores
#1370528 socnetv cannot build on non-x86-based architectures
#1364320 remove SRS pdf and fix spelling errors in Code
#1364361 SocNetV does not remember last directory used by user
#1378346 Cannot change size and value of a node
* New datasets:
- Stephenson and Zelen (1989): Network of 40 AIDS patients
- Stephenson and Zelen (1989): IC test dataset, 5 actors
- Wasserman and Faust: star, circle and line graphs of 7 actors