Exploring and understanding relationships

Abstract

This chapter provides an overview of the methodology of social network analysis (SNA) and a framework for understanding the next four chapters, which are case studies illustrating the application of SNA. 3 Exploring and Understanding Relationships Maryann M. DurlandAlthough the process of doing social network analysis (SNA) is similar to traditional research and evaluation design, it is in the details that the two traditions diverge. This chapter describes two areas of differences: (1) the framework for doing SNA and (2) data collection, analysis, and specific measures. SNA looks and sounds different from traditional methodologies (Hanneman, 2001). Two examples are the array of data and the language of analysis. At the data level, conventional data consist of columns of measurements on an attribute variable and rows of cases or subjects. This data analysis array is rectangular. The language of conventional analysis consists of terms such as scores, comparison of how subjects are similar or dissimilar across variables or how the variables are similar or dissimilar across the subjects. Network data have a square array. The rows, as in conventional data, are subjects or actors. The columns are the same set of actors. The measurement in each cell is the measure of the existence or degree of a relationship between the two actors. Though network analysts make row and column comparisons similar to conventional analysis, what is different is the holistic analysis of the data. The language of SNA includes terms such as density, cliques, and block models.SNA is about relationships and how to measure them. Results are in the form of both numerical data and a visual image called a sociogram or social map.

Factors Determining Peer Status in Outdoor Adventure Groups

“…Social network analysis data show the relationship structure within a group and include a measure of prestige. The prestige statistic is reported on a 0-1 scale based on the peer selections and the overall centrality of an individual within a social network in comparison to others in a network (Durland, 2005). The prestige statistic considers the number of incoming links along with the links of other individuals within the social network, assuming that an individual's importance is based to some degree on the prestige of the those directly connected to that individual (Rusinowska, Berghammer, de Swart, & Grabisch, 2011).…”

Evaluating Virtual Collaborative Learning platforms using Social Network Analysis

“…In contrast to simple statistical data, like counts and frequencies of posts and visits provided by common Learning Management Systems (LMS), Social Network Analysis allows the calculation of different network metrics for comprehensive investigation of social interactions, like cohesion of a learning community, students' participation in the course, and their position and importance in the network [19]. Thus, Social Network Analysis offers flexible and comfortable instruments for instructors, and also for students, to understand the social interaction of educational group members [20] , [21] .…”

A scoping review on the current and potential use of social network analysis for evaluation purposes

“…An important step in the design and application of SNA is the meaningful operationalization and specification of the network, actors and relations; that is, in line with the evaluation objectives and explanatory theories being used (Borgatti and Halgin, 2011). First, we must define the boundaries within which relationships will be measured (Durland, 2005a). Sometimes the network is finite and bounded by clear, formal criteria such as membership status (e.g.…”