UCINET 是一套全面的分析數據,及其他一維和二維的數據分析,可讀寫多種不同的格式化文字檔案,以及EXCEL的檔案。最高可處理32767節點。社會網絡分析方法包括核心措施、鑑定小組、分析角色、圖論基礎、排列型統計分析。另外包含強大的矩陣分析程式,例如矩陣代數、多元統計。
UCINET(University of California of Irvine Network Programms)由於其使用上較簡單,不論對初學者或專家同樣方便。UCINET如其他的網絡分析軟體,它處理的原始Data Set必須是由研究者所coding的actor-actor或actor-issue 矩陣資料,透過個人與個人或個人與事件間的"關係",電腦乃能辨識其處理的分析單位,並且透過不同的指令來作不同的分析,當然,如SPSS和SAS一般,UCINET原始資料的基本性質也決定了分析的層次,不過UCINET也有可能對資料作某種程度的轉型 (Transformation)。
Version 6.722-6.720
Changes
- Network|Whole Networks|Transitivity changed to include additional outputs
- Defaults changed in Network|Core Periphery|Categorical to make it faster on average
- Transform|Aggregate|Block rewritten to run in 64-bit mode
Fixes
- The structural holes routine in both the menu and command line developed a bug in 6.720, which was causing crashes. It has been fixed.
- The combined 32/64 bit installer was changed in hopes of fixing a weird problem in which the 32-bit ucinet would not start because it was missing some dlls (which the user could see were in fact present).
- Changed the DL editor so that after pressing New it puts the grid in input mode
- Windows operating system Vista or later. If you have a Mac or Linux, you can run UCINET via BootCamp, VMFusion Ware, Parallels or Wine.
- 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.
It assumes that the software has been installed with the data in the folder C:\Program Files\Analytic Technologies\Ucinet 6\DataFiles and this has been left as the default directory.
When UCINET is started the following window appears.
The submenu buttons give access to all of the routines in UCINET and these are grouped into File, Data, Transform, Tools, Network, Visualize, Options and Help. Note that the buttons located below these are simply fast ways of calling routines in the submenus. The default directory given at the bottom is where UCINET picks up any data and stores any files (unless otherwise specified) this directory can be changed by clicking on the button to the right.
Running a routine
To run a UCINET routine we usually need to specify a UCINET dataset and give some parameters. Where possible UCINET selects some default parameters which the user can change if required. Note that UCINET comes with a number of standard datasets and these will be located in the default directory. When a routine has been run there is some textual output which appears on the screen and usually a UCINET datafile contain the results that again will be stored in the default directory.
We shall run the degree centrality routine to calculate the centralities of all the actors in a standard UCINET dataset called TARO. First we highlight Network>Centrality>Degree and then click
This will bring up a box as follows
If you click on the help button then a help screen will open which looks like this. The help file gives a detailed description of the routine, explains the parameters and describes the output that will appear in the log file and on the screen.