Icon of program: NetDraw

NetDraw for Windows

Used NetDraw for Windows?

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Editors’ Review

Download.com staff
NetDraw is a free program designed for visualizing 1-mode and 2-mode social networks. It supports multiple relations and customizable node attributes. The software efficiently handles large datasets, especially with its VNA file format.

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  • Pros

    • Free to use visualization program.
    • Visualizes 1-mode and 2-mode social network data.
    • Customizes node appearance using attributes (color, shape, size).
    • Exports visualizations to common image formats (JPG, GIF, BMP).
    • Efficiently handles large sparse networks up to 10,000 nodes.

  • Cons

    • Optimal large file handling requires VNA format.
    • Performance for large, dense networks is not specified.
    • RAM requirements vary significantly based on network sparsity.
Icon of program: NetDraw

NetDraw for Windows

Used NetDraw for Windows?

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Full Specifications

GENERAL
Release
Latest update
Version
2.054
OPERATING SYSTEMS
Platform
Windows
Operating System
  • Windows XP
  • Windows 10
  • Windows 2000
Additional Requirements
None
POPULARITY
Total Downloads
2,566
Downloads Last Week
0
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Developer’s Description

By Analytic Technologies
Draw and display organizational networks.
NetDraw is a free program written by Steve Borgatti for visualizing both 1-mode and 2-mode social network data. It can handle multiple relations at the same time, and can use node attributes to set colors, shapes, and sizes of nodes. Pictures can be saved in metafile, jpg, gif and bitmap formats. The program reads UCINET system files, UCINET DL files, Pajek files, and its own VNA format (which allows saving network and attribute data together, along with layout information like spatial coordinates, colors, etc.). IMPORTANT: If you format data as a VNA file, NETDRAW can handle *very* large files. For example, sparse networks of 3500 nodes are very practical on a machine with 1GB of RAM (more is better). 10,000 nodes works fine with 2GB of RAM (assuming it is very sparse, of course).
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