New! UCINET-oriented book on social network analysis now available! See details.
UCINET 6 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.
If you use the software, please cite it. Here is a sample citation:
Borgatti, S.P., Everett, M.G. and Freeman, L.C. 2002. Ucinet for Windows: Software for Social Network Analysis. Harvard, MA: Analytic Technologies.
The program can be downloaded and used for free for 90 days. In addition, students can purchase the downloaded program for $40. Faculty and government can purchase the downloaded program for $150, and all others pay $250. Site licenses and extremely generous volume discounts are available.
Note that all purchases are provided as electronic downloads. If necessary you can order a CD from us for an exorbitant fee, but there is no reason to do this. Purchasers of the software are welcome to burn their own CDs at will. They are also free to download the program to all of their computers.
For more details, including questions about taxes, shipping costs, payment methods, etc., please visit the Order Info page.
Requirements and Specifications
Windows operating system Vista or later. If you have a Mac or Linux, you can run UCINET via BootCamp, VMFusion Ware, Parallels or Wine. See our FAQ on this.
The 32-bit version is the standard one and runs on both 32bit and 64bit Windows systems. A limited 64-bit version is available but does not have all UCINET functions
100mb of disk space for the program itself (not including your data)
The more RAM the better, but 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 try experimental 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 about 2 million 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, degree centrality can be run on networks of tens of thousands of nodes, and most graph theoretic routines run faster when you have very few ties, no matter how many nodes you have.
Week-long workshop on SNAThe LINKS Center at the University of Kentucky is offering its annual 1-week summer workshop on social network analysis June 6-10, 2016 on the University of Kentucky campus ...
Posted Mar 15, 2016, 12:54 PM by Steve Borgatti
UCINET 6.620 | 13 June, 2016Fixed important bug in Data|Affiliations|Mode=Rows. When given a multi-matrix dataset as input, it was writing out each 1-mode projection twice.Replaced k-plex routine in ...
Posted Jun 13, 2016, 11:12 AM by Steve Borgatti