SNA TIG Week: Maryann Durland on Measurements and Sociograms in Social Network Analysis – Why Both Are Important
Hi AEA 365er’s. I’m Maryann Durland, founding Chair of the Social Network Analysis (SNA) AEA Topical Interest Group (TIG) and an independent consultant with specialization in SNA. My topic in this SNA TIG series is about the importance of both measurements (numeric data) and sociograms (visual graphics) in SNA.
Lessons Learned: The field of sociometrics and sociograms began in the 1930s with the work of Jacob Moreno. Over the following decades, research in diverse and fragmented fields sporadically built a body of knowledge, theories and tools related to SNA measurement or visualization. The many fragmented areas began to come together to form a coherent research paradigm during the early 2000s. Freeman (2004) describes the features that define the current SNA paradigm:
- SNA is structural in nature
- SNA is grounded in empirical data
- SNA draws heavily on graphic imagery
- SNA relies on mathematical and/or computational models
With SNA, measures and graphic imagery are intertwined in understanding the meaning of a network. Measures can be ranked or compared across networks, when appropriate. Graphic imagery places positions within a visual structure, based on established criteria. Graphic imagery also illustrates the structural features of the network, such as isolates (individuals who are not connected to anyone else in a network) and bridges (lines that keep the network connections between others).
Some structural features can be measured; others need to be observed. Visual imagery may indicate where measures interact with structural features.
Consider two individuals who both have a Freeman Indegree measure of 11 for communication relationships within the same network (Indegree is the number of times a person is selected by others). Individual A is connected to 11 others who are connected to many branches, small cliques, and other clusters throughout the larger network, while individual B is only connected to the 11 members of one clique without further connections to the larger network. Though the Indegree measure suggests both are similar, the imagery illustrates the sharp differences in structural location of the two individuals.
Without graphics and the inclusion of structural features, SNA measures become attributes of individuals and as such tend to be treated within traditional research paradigms. A network study requires both measures and graphic imagery to account for the structural features of the network.
Freeman, L.C. (2004). The Development of Social Network Analysis: A Study in the Sociology of Science. Vancouver, BC Canada: Empirical Press.
The American Evaluation Association is celebrating SNA TIG Week with our colleagues in the Social Network Analysis AEA Topical Interest Group. The contributions all this week to aea365 come from our SNA TIG members and you can learn more about their work via the SNA TIG sessions at AEA’s annual conference. Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.