News

SocNetV 2.4 Released

Feb 28, 2018

Dimitris

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.

  

• 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.

  

• 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.

  

• 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.

  

• 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.

  

• 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

Jul 5, 2017

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:

Newer posts