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SocNetV v3.4 Released

Dimitris

SocNetV v3.4 Screenshot

SocNetV v3.4 released! 🎉

We are happy to announce the release of SocNetV v3.4, the latest version of our cross-platform social network analysis and visualization software.

This release focuses on stability and correctness, with a comprehensive overhaul of progress/cancel handling across all computation paths, significant parser and layout fixes, and the completion of the IO/Parser architectural refactor started in v3.3.

🔍 What’s New in SocNetV v3.4?

⏹ Comprehensive Cancel support in progress dialogs (#52)

This has been one of the longest-standing issues in SocNetV. In v3.4, the Cancel button in progress dialogs now works correctly and consistently across all computation paths:

  • Centrality and prestige computations
  • Reachability and walks
  • Matrix and report generation
  • Layout algorithms (including Kamada-Kawai)
  • Clique census and subgraph construction
  • All random network generators (Erdős–Rényi, Small-World, Scale-Free, Regular, Lattice, Ring-Lattice)

📐 Force-directed layout fixes

  • Fixed division-by-zero, NaN/Inf, and logic errors in the Kamada-Kawai layout (#198)
  • Fixed Fruchterman-Reingold simmering temperature derivation from canvas size (#199)
  • Faithful reimplementation of the Eades (1984) Spring Embedder (#207)
  • Batched node position emissions in all force-directed layouts for smoother rendering (#205, #206)

📥 Parser and IO fixes

Many import/export edge cases resolved:

  • Pajek *Matrix header parsing for relation labels (#188)
  • Pajek multirelational export as *Matrix blocks (#184)
  • Normalized quoted relation names in Pajek headers (#185)
  • Inline GML node/edge block parsing (#186)
  • Arc doubling when loading undirected DOT graphs (#187)
  • Platform-dependent weighted=true from uninitialized variable in DOT parser (#189)
  • Two-mode sociomatrix import now correctly handled in the parser (#15)

📊 Centrality fixes

  • Fixed eigenvector centrality isolate reset and N==0 handling (#202)
  • Fixed Information Centrality isolate handling and degenerate cases (#201)
  • Fixed clustering coefficient computation for directed networks (#58)
  • Fixed wrong weighted flag when switching relations (#82)

🏗 Completed IO/Parser refactor (WS4)

The architectural refactor of the IO/Parser layer, started in v3.3, is now complete:

  • The monolithic parser.cpp (~5500 LOC) has been split into focused per-format modules: edgelist, adjacency, UCINET DL, DOT, GML, Pajek, GraphML
  • An explicit IGraphParseSink mutation surface replaces the old Qt signal fan-out
  • GUI and headless (socnetv-cli) loading paths now share an identical, deterministic mutation pipeline

🧪 Expanded regression harness

  • New io_roundtrip kernel (schema v5) for IO/parser regression protection
  • Many new golden comparison cases and small deterministic test networks
  • New helper scripts: run_io_roundtrip_shipped_datasets.sh, run_golden_io_roundtrip.sh

🌐 i18n

  • Added update_translations.sh script for maintainers
  • Updated DE and ES translation files

🛠 Build and packaging

  • Debian packaging switched to CMake build system
  • RPM spec updated for CMake (Fedora, openSUSE, Mageia)
  • CMake now generates .qm translation files via qt_add_lrelease

We’d like to thank our contributors and users for reporting issues, testing fixes, and helping SocNetV improve with every release. 🙏

Download SocNetV v3.4 from our Download page and let us know what you think!

Happy analyzing!
— The SocNetV Team

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!