Social network analysis is focused on uncovering the patterning of people's interaction. 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. 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.
That 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. And, beginning in the 1930s, a systematic approach to theory and research, based on that notion, began to emerge. In 1934 Jacob Moreno introduced the ideas and tools of sociometry. And at the end of World War II, Alex Bavelas founded the Group Networks Laboratory at M.I.T.
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, and (2) it is grounded in the systematic analysis of empirical data. It was not until the 1970s, therefore--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. It has found important applications in organizational behavior, inter-organizational relations, the spread of contagious diseases, mental health, social support, the diffusion of information and animal social organization. Today it has become an international effort with its own professional organizations, text books, journals, research centers, training centers and computer programs designed specifically to facilitate the analysis of structural data.
The information on this page was contributed by Lin Freeman