Scott Degraffenreid is a practicing Social Network Analyst, and one of the few who are not employed by the military and government.
Social Network Analysts study very large data sets, looking at hundreds of influencing factors and billions of data points. Using complex computer models running millions of calculations, specific behavior and location patterns are discovered and mapped.
This is much more accurate than surveys as it measures actual behavior.
Social Network Analysts believe that how an individual lives depends in large part on how that individual is tied into the larger web of social connections. Many believe, moreover, that the success or failure of societies and organizations often depends on the patterning of their internal structure.
From the outset, the network approach to the study of behavior has involved two commitments:
(1) It is guided by formal theory organized in mathematical terms
(2) It is grounded in the systematic analysis of empirical data
It has found important applications in organizational behavior, inter-organizational relations, the spread of contagious diseases, mental health, social support, the diffusion of information, animal social organization and business /marketing development.
• Social Network Analysis is a diagnostic tool that gives you a bird’s-eye view of your organization’s knowledge capital.
• An organization’s collective knowledge and experience, embodied in informal networks, is its most valuable asset during times of change.
• With little effort, small but pivotal changes have substantial impact on business performance and therefore on the bottom line.
• Network Analysis is the most effective method of saving money because you are targeting the causal and most costly asset: human capital, rather than treating symptoms.
History of Social Network Analysis
Social Network Analysis emerged from the need to understand the complexities of human behavior in groups at a more objective and scientific level than either psychology or sociology. Social Network Analysis is devoted to identifying and unraveling the intricate patterns of people and their networks. It is about the kind of patterning that Roger Brown described when he wrote:
"Social structure becomes actually visible in an anthill; the movements and contacts one sees are not random but patterned. We should also be able to see structure in the life of an American community if we had a sufficiently remote vantage point, a point from which persons would appear to be small moving dots ... We should see that these dots do not randomly approach one another, that some are usually together, some meet often, some never ... If one could get far enough away from it human life would become pure pattern."
Network analysis is based on the intuitive notion that these patterns are important features of the lives of the individuals who display them.
This kind of intuition is probably as old as humankind. It is implied, for example, by the relative stress put on descent lists in the Bible. Beginning in the 1930s, a systematic approach to theory and research, based on this notion, began to emerge. In 1934, Jacob Moreno introduced the ideas and tools of sociometry. At the end of World War II, Alex Bavelas founded the Group Networks Laboratory at M.I.T.
It was not until the 1970s, when modern discrete combinatorics (particularly graph theory) experienced rapid development and relatively powerful computers became readily available, that the study of Social Networks really began to take off as an interdisciplinary specialty. Since then its growth has been rapid. Today it has become an international effort with its own professional organizations, textbooks, journals, research centers, training centers and computer programs designed specifically to facilitate the analysis of structural data.