The following presents Social Network Analysis, a statistical method of analyzing social networks based on Multi-dimensional Scaling (MDS). A description of social network analysis, what it is used for, and how data are typically collected are discussed.
Social network analysis is a statistical method used to discover patterning within an individual's interactions with another. Social structure can be visible revealing a patterned interaction. Network analysis considers the importance of these patterns in the lives of individuals and the overall social network. The network approach to studying behavior includes a formal theory that is organized in mathematical terms and it is based on a systematic analysis of empirical data (International Network for Social Network Analysis [INSNA], 2004).
Social network analysis allows for empirical investigation and theoretical analysis as well as application of network techniques to organizational interventions (Nelson, 1988). This analysis is based on Multidimensional Scaling (MDS), which includes mathematical techniques that allow for the discovery of patterns. An example of MDS use is found in political science. MDSD can locate political candidates with a map showing spatial configurations to determine answers to questions such as "What identifiable features can we discern in the varying evaluations of the candidates that can help us understand what led individual citizens to their decisions" (Kruskal & Wish, Series/Number 07-001, p. 5). In this instance MDS would reduce the data about the candidates to two dimensions with key differences at opposite ends, thus developing indicators to be measured in future elections. Thus MDS refers to techniques that use proximities among objects for input. Proximity refers to similarity or differences between objects and the output in this case is a spatial representation with geometric configurations of points. This map shows the hidden st...