The NOESIS Network Analyzer

Our user-friendly tool for the analysis and visualization of complex networks, freely available for download at

The NOESIS Network Analyzer features an improved network renderer based on JavaFX technology that offers much better performance than traditional Swing-based applications.

NOESIS Network Analyzer main features

  • Supported network file formats (for analyzing your own networks):
    • GML
    • GraphML
    • GDF

  • Adjustable network visualization:
    • NEW! Improved JavaFX network renderer.
    • Drag & drop graphical user interface.
    • Automatic layout methods (Fruchterman-Reingold, Kamada-Kawai, hierarchical, radial, random, and regular layouts).
    • Multiple visualization options (styles, colors & sizes).
    • Export network images in SVG, PNG, or JPEG format.

  • Network models:
    • Random networks: Erdös-Renyi, Gilbert, Watts-Strogatz, Barabasi-Albert, and Price models.
    • Regular networks: Star, ring, tandem, mesh, toroidal, hypercube, and binary tree networks.

  • Network analysis techniques:
    • Network structural properties (degree, degree assortativity, eccentricity, average path length, closeness, decay, betweenness, PageRank, HITS, eigenvector centrality, Katz centrality, clustering coefficient, connected components, link betweenness, link embeddedness, link neighborhood overlap...).
    • Community detection methods (Kernighan-Lin partitioning; Newman-Girvan & Radicchi hierarchical community detection; single-link, average-link & complete link hierarchical clustering; fast & multi-step greedy modularity-based community detection; EIG1, KNSC1 & UKMeans spectral community detection, and BigCLAM overlapping community detection).
    • Link scoring & prediction methods (common neighbors, Adamic-Adar score, resource allocation, Jaccard score, preferential attachment, Salton score, Sorensen score, hub-promoted & hub-depressed scores, local & global Leicht-Holme-Newman score, Katz score, random walks & random walks with restarts, flow propagation, pseudoinverse Laplacian score, average commute time score & random forest kernel score).

System requirements: Java Runtime Environment version 8 (JRE8) or later needed for the NOESIS JavaFX renderer. The Java runtime and development kit can be downloaded for Windows, macOS and Linux directly from the official Oracle web page,

NOTE: The efficient implementation of network analysis techniques makes use of multiple cores in multicore processors when available.

Network visualization

Gnutella P2P network

International trade network

Random scale-free network (Barabasi-Albert model)

Victor Hugo's "Les Misérables" link scoring: common neighbours, preferential attachment score & Katz index

You can access these methods using the "Analysis > Links > Link prediction" menu for predicting new links or the "Analysis > Links > Link scoring"menu for evaluating existing ones.