SocNetV v2.2 Released with Cluster Analysis, Eigenvector Centrality, and More!
We are pleased to announce that a new version of your favorite social network analysis and visualization software application has been released. SocNetV version 2.2, codenamed “beyond”, brings many new features and is now available for Windows, Mac OS X, and Linux. Visit the Downloads page to get it!
What’s New in SocNetV v2.2?
Hierarchical Clustering Analysis (HCA)
SocNetV now performs hierarchical agglomerative cluster analysis on social networks using these methods:
- Single-Linkage (minimum)
- Complete-Linkage (maximum)
- Average-Linkage (UPGMA)
You can compute the Structural Equivalence matrix using adjacency or geodesic distance matrices with user-selected metrics such as Euclidean, Manhattan, and Jaccard distances.
Results include:
- A list of clusters per level.
- A dendrogram of the cluster hierarchy in SVG format.
Eigenvector Centrality
Version 2.2 introduces Eigenvector Centrality, which measures the influence of a node in a network based on the leading eigenvector of the adjacency matrix.
Use this metric for network analysis or embedding radial/level layouts.
Pearson Product-Moment Correlation Coefficients
SocNetV now computes Pearson Correlation Coefficients to correlate actor profiles (ties or distances). Results are displayed as a correlation matrix.
Actor Similarity
Compare pairwise tie/distance profiles of actors to produce a similarity matrix using measures like:
- Simple Matching
- Jaccard
- Hamming
- Cosine Similarity
- Euclidean Distance
Maximal Clique Census
Using the Bron–Kerbosch algorithm, SocNetV finds all maximal cliques in undirected or directed graphs. The clique census report includes useful statistics, co-membership information, and dendrograms.
Additional Features
Cocitation Analysis
- Compute Cocitation Matrices.
- Create Cocitation Networks, where actors are connected if they are cited by common neighbors.
Symmetrize Edges by Strong Ties
Create new relations using only strong, reciprocal ties.
Multi-relational GraphML Support
Read and write .graphml files with multiple relations.
GML and Pajek Support
Support for GML formatted data and multi-relational Pajek files.
Performance Improvements
- Faster matrix multiplication using optimized algorithms.
- Enhanced adjacency matrix plotting with Unicode characters.
Bug Fixes and Notices
- Resolved various issues like incorrect distances in weighted networks, edge labels not saving, and more.
- New dataset: Petersen Graph.
- Transformed Krackhardt’s High-tech Managers and Zachary Karate Club into multirelational datasets.
Important Notices:
- Project’s new domain: https://socnetv.org
- Code and files are now hosted on GitHub.
Download SocNetV v2.2 today and enjoy the new features and improvements!