Social network analysis is a methodology for studying relational or relationship data and is grounded in understanding and applying the methodology within a context of networks. Social network analysis provides the tools for exploring the fit of individuals and subgroups within a network and for measuring the structural characteristics of the network, subgroups, and individuals. Though it has an historical thread through quantitative paradigms, it is conceptually and methodologically distinct from traditional statistical analyses.
About Social Network Analysis in Evaluation
Use of social network analysis in evaluation has increased significantly over the last 12 years. Examples of its use can be found in evaluations as diverse as education (Penuel, Sussex, Korbak, and Hoadley, 2006), programs addressing disparity issues among health insurance providers (Gold, Doreian, & Taylor, 2008), children’s health insurance initiatives (Valente, Coronges, Stevens, & Cousineau, 2008), school-level violence prevention programs (Cross, Dickman, Newman-Gonchar, & Fagan, 2009), and state-level tobacco control partnerships (Harris, Luke, Burke, & Mueller, 2008; Krauss Mueller, & Luke, 2004).
Further explanations of SNA methods, particularly as applied to program evaluation, can be found in Durland and Fredericks (2005), Luke and Harris (2007), and Provan, Veazie, Staten, and Teufel-Shone (2005). Furthermore, SNA is used for evaluation of research and product development (Mote, Jordan, Hage, & Whitestone, 2007), for studying knowledge generation and flow in the basic science community (Mohrman, Galbraith, & Monge, 2004), and for assessment of interdisciplinary collaborations (Haines, Godley, & Hawe, 2010).
SNA is not a new field, though with the advance of computer programs for calculating the SNA measures it has the feel of a relatively young field (see Linton Freeman’s The Development of Social Network Analysis, 2004). Since the late 1990’s SNA has been expanding and is a very dynamic area for theory and research.