UCINET

Originally developed by Linton Freeman, UCINET is a comprehensive social network analysis software program. Designed by Steve Borgatti, Martin Everett, and Linton Freeman, Version 6 (the current version as of 2017) is a menu-driven Windows-based program to be used even by non-tech-savvy researchers. Mostly used by social scientists in the field of sociology and management, UCINET also has growing users in the fields of education, health, and life sciences. In general, UCINET is used to analyze sociometric survey data; however, it is also used to analyze other one-mode and two-mode matrix data. UCINET features a number of metric routines used to describe positions of nodes, dyads, groups, and whole networks.

Routine functions of UCINET include algorithmic outputs unique to social network analysis methods such as measures of centrality (e.g., degree, betweenness, closeness, and eigenvector) and cohesion (e.g., density, fragmentation, and components), permutation-based statistical analysis (e.g., t tests, analysis of variance, and regression), as well as algebraic and multivariate statistical matrix analyses. Built in to UCINET is the visualization program NetDraw. Developed by Borgatti, NetDraw works in tandem with UCINET to draw diagrams or visualize social networks.

Major Routine Functions of UCINET

Typical users of UCINET are those familiar with the fundamental theories and methods associated with network analysis. Social capital and diffusion of innovation theories ground the majority of social network research. For example, social capital studies are geared toward the investigation of how social connections support or constrain opportunity while diffusion of innovation research is concerned with the exploration of how knowledge and resources spread. UCINET is useful to researchers interested in these theories as the program is designed for the mathematical and visual analysis of network data.

UCINET has the capacity to read and write a variety of differently formatted data and text file types, as in Pajek, Krackplot, Negopy, and the VNA format used by NetDraw. Unlike other social network analysis programs, UCINET can also import and export Microsoft Excel files. At maximum, the program can handle network data comprising 32,767 nodes or actors; however, many of the routine procedures become less efficient with around 5,000 to 100,000 nodes.

UCINET requires a data set for most routine functions. As a result, the program stores and describes almost all data as collections of one or more matrices. Examples of data formats are described in Figure 1.

Figure 1 UCINET data formats. This table provides descriptions and examples about UCINET acceptable data formats. Adapted from Borgatti (2014).