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SocNetV v1.9 released - Bug Fixes and Speed Increase

Dimitris

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.

SocNetV v1.8 Released with Scale-Free Network Generator

Dimitris

A new version of SocNetV has just been released with a couple of nice new features.

Clique Computation Routine

SocNetV v1.8 includes a revamped clique computation routine with an updated report. The new “clique census” report provides:

  • Aggregate counts of cliques (up to clique number 4).
  • Disaggregation by vertex and co-membership information.

Clique Census Example

Scale-Free Network Generator

This version introduces the ability to generate scale-free random networks/graphs using the Barabási–Albert (BA) model, which employs a preferential attachment mechanism.

The algorithm starts with ( m_0 ) connected nodes (default: 1). At each step, a new node is added with ( m ) edges to existing nodes. The probability ( p_i ) that the n

SocNetV v1.7 Released with Lots of Goodies!

Dimitris

A new SocNetV release hit the road today. Version 1.7 solves a number of bugs and brings lots of interesting and useful new features to our users. Binaries for Windows, Mac, and Linux are already available on the project’s Downloads page. Here’s what’s new…

New Node Properties Dialog

Up to now, editing a node required selecting each property individually (e.g., color, label). In version 1.7, a new Node Properties dialog consolidates all node editing options in one place. Simply right-click a node and select “Node Properties” (or press Ctrl+X, Ctrl+P).

Node Properties Dialog

In the Node Properties dialog, you can:

  • Enter a label.
  • Adjust the node size.
  • Edit the node color.
  • Choose a node shape (e.g., rectangle, circle).

Changes are applied in one step and previewed live on the canvas. For instance, selecting the color button brings up a Colors dialog for easy color selection:

Colors Dialog

Group Node Editing

SocNetV v1.7 introduces the ability to select and edit multiple nodes simultaneously. Select nodes by left-clicking and dragging to draw a selection rectangle. Then, right-click on a selected node or the canvas to open the context menu and choose “Node Properties.”

Group Node Selection

The dialog is identical to the single Node Properties dialog, but changes apply to all selected nodes. If you label multiple nodes, SocNetV appends the node number to each label:

Group Node Labeling

Select All and Select None

New shortcuts make it easier to select all nodes (Ctrl+A) or deselect all nodes (Ctrl+Shift+A).

Select All Shortcut

File Previewer

A major improvement in v1.7 is the introduction of a Network File Previewer, addressing issues with loading files saved in different codepages (e.g., non-Latin characters). The previewer allows users to select the correct encoding before loading the file.

File Previewer

With the File Previewer, users can:

  • Preview the file in various encodings.
  • Ensure proper display of all characters before loading.

Preview Encodings

Press “OK” to load the file and display the network on the canvas:

File Loaded

Notes on Encoding

  • Linux/Mac: Use UTF-8, except when loading files saved in Windows.
  • Windows: Use Windows-1253 for most cases or KOI8-R for Russian characters.
  • Default: SocNetV saves files in UTF-8 by default.

Bug Fixes and Changelog

SocNetV v1.7 resolves several bugs and introduces many improvements. For a full list of changes, visit the ChangeLog.

If you spot a bug, report it here. Feature requests are welcome on our blueprints listing.

Enjoy version 1.7!

SocNetV v1.6 Released with a Working Web Crawler

Dimitris

The SocNetV project has just released its latest version 1.6. Binaries for Windows, Mac OS X, and Linux are available from the Downloads menu.

Revamped Web Crawler

The new version brings back the web crawler feature, which had been disabled in the 1.x series so far.

To start the web crawler:

  • Go to Network -> Web Crawler or press Shift+C.

A dialog will appear where you:

  • Enter the initial web page (seed).
  • Set the maximum number of nodes/pages (default is 600).
  • Choose the types of links to crawl: internal, external, or both. By default, the crawler processes both.

Web Crawler Dialog

How It Works

The new web crawler is significantly improved compared to the 0.x releases. It consists of two components:

  1. Spider: Visits the specified initial URL, downloads its HTML, and processes it.
  2. Parser: Scans the downloaded HTML for href links to internal or external pages and adds them to a queue of URLs (the “frontier”).

The spider and parser run on separate threads, ensuring faster execution.

As URLs are added to the queue, the spider visits them, downloads their HTML, and the parser extracts more links, continuing the cycle.

Crawler in Action

The process is multithreaded and completes within seconds, even for large sets like 1,000 URLs.

Results

The crawler creates a network of all visited webpages as nodes and their links as edges. By default, node sizes are proportional to their outDegree, making patterns visible immediately.

Crawler Output

From there, you can analyze the network using the SNA tools provided by SocNetV.

Analyzing the Crawled Network

Note: The parser searches for href links only in the body section of the HTML.

Explore and analyze networks effortlessly with the enhanced capabilities of SocNetV v1.6!

SocNetV as "Intelligence" Source for Dolphin-Site Operators

Dimitris

Can you use SocNetV to analyze a virtual “social network”? Yes, you can! For instance, you could analyze social interactions (e.g., mentions) between “friends” in a virtual network. Although SocNetV cannot directly grab data from private networks (its built-in web crawler is limited to publicly accessible data), if you extract the network data yourself and transform it into GraphML format, SocNetV can load and visualize the virtual network for analysis.

This approach is particularly useful for platforms like Dolphin, an open-source platform for social networks, and its mobile-friendly sibling Trident. These platforms support social connections, conversations, locations, and other social graph-related data types, which can be analyzed using SocNetV based on operator needs.

Example Use Case

Imagine an airline company launches a social network for its clients. By using SocNetV to analyze connections, discussion trends, and user posts, the company could:

  • Identify which routes are in demand.
  • Plan and optimize scheduling based on social data.
  • Target specific user segments with special offers.
  • Advertise these offers directly within the social network.

This innovative application of SocNetV showcases its potential as an “intelligence” source for network operators, enabling data-driven decision-making and enhanced user engagement.

Kudos to the Dolphin and Trident teams for exploring this exciting use case for SocNetV!