UCINET is a comprehensive package for the analysis of social network data as well as other 1-mode and 2-mode data. Can read and write a multitude of differently formatted text files, as well as Excel files. Can handle a maximum of 32,767 nodes (with some exceptions) although practically speaking many procedures get too slow around 5,000 - 10,000 nodes. Social network analysis methods include centrality measures, subgroup identification, role analysis, elementary graph theory, and permutation-based statistical analysis. In addition, the package has strong matrix analysis routines, such as matrix algebra and multivariate statistics.

UCINET for Windows is a software package for the analysis of social network data. It was developed by Lin Freeman, Martin Everett and Steve Borgatti. It comes with the NetDraw network visualization tool.

Requirements and Specifications

• Windows operating system Vista or later. If you have a Mac or Linux, you can run UCINET via a Windows emulator, such as Parallels or Oracle VM VirtualBox.
• 100mb of disk space for the program itself (not including your data)
• The installation program installs both a 32-bit version and a 64-bit version. The 32-bit version can't take advantage of more than 3GB of memory. If you have large data and a 64-bit version of Windows, you can use the 64-bit version, in which case 8GB of RAM or more would be useful. Remember, however, that even if a really large dataset fits in memory, it may take too long to analyze.
• While the absolute maximum network size is 32767 nodes, in practice most UCINET procedures are too slow to run networks larger than about 5000 nodes. However, this varies depending on the specific analysis and the sparseness of the network. For example, UCINET can calculate the geodesic distance between all pairs of points in a network of 5000 nodes and 1.25 million edges in 14 seconds. But beta centrality on the same network would take too long to be practical.