SocNetV v1.9 released - Bug Fixes and Speed Increase
The Social Network Visualizer project has just released version 1.9, which fixes many important bugs and brings a faster matrix inverse routine. Source code, Windows zipped executables, Mac OS image, and binary packages for major Linux distributions are as always available from the Downloads page.
Key Improvements
-
Faster Matrix Inverse Routine:
The matrix inverse algorithm now uses LU decomposition, greatly improving computation speed. This enhancement also affects the Information Centrality algorithm, which now runs in 1/10th of the time required in earlier SocNetV versions. -
Revamped PageRank Prestige Algorithm:
Up to version 1.8, the PageRank algorithm used the original Page & Brin formula, leading to different results. Starting from this version, SocNetV uses the correct formula and computes comparable results. Additionally, the initial PageRank score of each node is now set to 1/N.
Closed Bugs in Version 1.9
- #1463069: Wrong average distance when there are isolates.
- #1365037: Certain sparse matrices crash SocNetV on the invertMatrix method.
- #1365582: CentralityInformation() is slow when network size (N > 100).
- #1463095: Edge filter works but the user cannot undo.
- #1464422: Incorrect PageRank results.
- #1464430: SocNetV refuses to read Pajek files not starting with
*Network. - #1465774: Edges do not always follow relations.
- #1463082: Edge color change does not take effect.
- #1464418: SocNetV crashes during PageRank computation on isolated nodes.
With these enhancements and fixes, SocNetV v1.9 ensures faster and more reliable performance for your social network analysis tasks.