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SocNetV 2.4 Released

Dimitris

SocNetV 2.4 Screenshot

Description

The Social Network Visualizer project released today a brand new version of our favorite social network analysis and visualization software application. SocNetV version 2.4, released on Feb 28, is a major upgrade bringing lots of new features. The new version is available for Windows, macOS, and Linux from the Downloads page.

New Features and Improvements

  • Kamada-Kawai Layout Model: This model treats the network as a dynamic system where actors are connected by “springs.” The layout optimizes the graph based on spring energy, minimizing the imbalance between desired and actual distances.

    Kamada-Kawai Layout

  • Node Colors by Prominence Score Visualization: In this version, SocNetV can visualize the prominence score of each actor by changing their color. The color reflects how important the actor is in the network, with red indicating high prominence and blue indicating lower prominence.

    Node Color by Prominence

  • Reciprocated Edges in Directed Networks: SocNetV now displays reciprocated edges in a single line with two arrows instead of two separate lines, reducing memory consumption and making the visualization more appealing.

    Reciprocated Edges

  • Improved Memory Consumption: The new version optimizes memory usage when loading large networks, improving performance for graphs with more than 2,000 edges.

  • Web Crawler Improvements: The web crawler dialog and algorithm have been enhanced with new options, including the ability to specify link patterns to include/exclude and control the delay between requests.

    Web Crawler

  • Improved Statistics Panel: The statistics panel now uses simpler text to display statistics more efficiently. It also shows edge direction weights for reciprocated edges in directed networks.

  • Performance Options in Settings: New performance options in the Settings dialog allow you to enable/disable features of the Qt GraphicsView, such as anti-aliasing and edge highlighting. Disabling certain options can significantly boost performance for large networks.

    Performance Options

  • Improved UCINET Format Support: SocNetV now supports reading two-mode UCINET files formatted in fullmatrix. These files declare both NR (nodes) and NC (columns) variables.

  • Improved Stability: Many bugs have been fixed, and random crashes were resolved. Below are some of the bugs that were fixed:

    • #40: Wrong BC scores in weighted networks
    • #54: Incorrect edge weight after user confirmation
    • #38: Disabling isolate nodes not reflected in distance matrix report
    • #41: Incorrect variance in clustering coefficient
    • #33: Missing Radial/Level Layout by Eigenvector Centrality
    • #48: Eccentricity scores for isolated nodes
    • #34: No menu options for Node Size layout by Prominence index
    • #56: Edge offset issues when resizing nodes
    • #46: Crashes after disabling isolated nodes in distance matrix
    • #42: Improved progress dialogs
    • #44: Crash when searching after node removal
    • #51: Web crawler crashes fixed
    • #60: Incorrect file extension when saving famous datasets
    • #61: “Save As” issue with GraphML format
    • #62: EdgeList1 formatted UCINET files not recognized
    • #63: Two-mode UCINET files unsupported
    • #65: Crashes in HCA with ill-defined input matrices
    • #36: HCA crashes with isolated nodes
    • #49: Connectedness method issues
    • #47: Extra columns in adjacency matrix report

Availability

SocNetV v2.4 is now available for Windows, macOS, and Linux. Go to the SocNetV Downloads page to get it!

SocNetV 2.3 Released

Dimitris

The Social Network Visualizer project is happy to announce that a brand new version of our favorite social network analysis and visualization software application has been released. SocNetV version 2.3, released on Jul 5, has the eloquent codename “fixer” and it is now available for Windows, Mac OS X, and Linux from the Downloads page.

What the new version brings to the users?

As usual with our odd-numbered minor versions, this is a bugfix release. While v2.2 brought a lot of new and important features, v2.3 focuses on stability and fixing bugs here and there. Nevertheless, there are a couple of new features as well, which you may find interesting for your network analysis endeavors:

Dyad and Actor/Ego Reciprocity

Reciprocity, denoted by ‘r,’ is a network cohesion index. It measures the likelihood of vertices in a directed network to be mutually linked. SocNetV v2.3 supports two different methods to index the degree of reciprocity in a social network:

  • Arc reciprocity: The fraction of reciprocated ties over all actual ties in the network.
  • Dyad reciprocity: The fraction of actor pairs that have reciprocated ties over all pairs of actors that have any connection.

In a directed network:

  • Arc reciprocity measures the proportion of directed edges that are bidirectional. If the reciprocity is 1, the adjacency matrix is structurally symmetric.
  • Dyad reciprocity measures the proportion of connected actor dyads that have bidirectional ties between them.

In an undirected graph, all edges are reciprocal, and the reciprocity of the graph is always 1.

You can compute reciprocity on undirected, directed, and weighted graphs from the toolbox/menu: Analyze > Cohesion > Reciprocity. The report is opened and displayed as usual in HTML format in your preferred web browser.

Zero-weighted Edge Support

In ordinary SNA, zero-weighted edges are thought to be meaningless, but a user pointed out that SocNetV was accepting and drawing zero-valued edges when opening edge list formatted files. This behavior was due to a bug.

The concept of an edge in SNA (and SocNetV) is that two actors (i) and (j) are “connected” (and an edge is drawn between them) only if there is a non-zero value at sociomatrix cell (A(i,j)). Thus, if (A(i,j) = 0), the actors are considered not directly connected, and no edge should be drawn between them.

This assumption has implications for computations: all centrality and matrix manipulation algorithms of network analysis implicitly compute their results using only non-zero (and some only positive) weighted edges.

To accommodate users who may need this functionality for visualization purposes, we implemented support for zero-weighted edges in v2.3. This functionality currently works only for weighted edge lists and for simple visualizations.

Zero-weighted Edge Color Selection

With the new feature above, the Settings dialog allows users to select a default edge color for zero-valued edges. Here is a screenshot:

SocNetV v2.3 Settings Dialog

SocNetV v2.2 Released with Cluster Analysis, Eigenvector Centrality, and More!

Dimitris

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.

HCA Dialog

Results include:

  • A list of clusters per level.
  • A dendrogram of the cluster hierarchy in SVG format.

HCA Results

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.

Eigenvector Centrality

Use this metric for network analysis or embedding radial/level layouts.

Eigenvector Layout

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.

Pearson Coefficients Dialog

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.

Clique Census Report

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.

Adjacency Matrix Plot

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:

Download SocNetV v2.2 today and enjoy the new features and improvements!

SocNetV v2.1 Released!

Dimitris

Today is a wonderful day because we are happy to announce that a brand-new version of our favorite social network analysis and visualization software application has been released. SocNetV version 2.1, released on September 28, 2016, has the codename “fixer” and is available for Windows, Mac OS X, and Linux from the Downloads page.

What’s New in SocNetV v2.1?

Faster and More Accurate Network Analysis Computation

  • Improved algorithms for social network analysis allow most metrics to be computed simultaneously. The results are saved and reused during the session, recalculating only when nodes, edges, or weights are modified.
  • Fixed metrics like PageRank Prestige (PRP) and Average Graph Distance (AGD) now produce accurate results.

New d-Regular Random Network Generator

  • The d-regular network generator has been rewritten and now generates both directed and undirected d-regular random networks without errors.

Improved UCINET Format Support

  • Fullmatrix format is now supported again. SocNetV already supports the edgelist format, ensuring compatibility with more datasets.

Better Network Visualization

  • Fixed issues with node and edge stacking on the canvas.
  • Corrected the display of edges with large weights to prevent overly thick lines.

Bug Fixes

  • #1624561: Network files with both arcs and edges are loaded as solely undirected nets.
  • #1622889: The d-regular generator does not produce random networks.
  • #1623812: After loading a new network file, the app behaves as if the network has changed.
  • #1624583: UCINET .dl files crash the app.
  • #1624750: Random new nodes can be drawn out of the canvas.
  • #1625831: Removing an edge in undirected graphs does not update the node outDegree.
  • #1627390: Wrong PageRank Prestige results in undirected nets.
  • #1627721: Incorrect average graph distance metric in disconnected networks.
  • #1628382: Edges with very large weights are drawn with huge line widths.
  • #1627213: Crashes when double-clicking on a target node after deleting the source node.
  • #1628170: Edge labeling with HTML special characters breaks GraphML files.
  • #1622891: Highlighted edges should have a larger z-index.
  • #1624352: The “Change Edge Color” dialog does not display the current edge color.
  • #1624360: Default edge color and node shape are incorrect in Edit menu dialogs.
  • #1628395: Incorrect z-value of nodes and edges caused cluttering.

Download SocNetV v2.1 today and, as always, have fun with your social network analysis projects!