Social network analysis is as much a perspective as it is a
set of tools. Rather than focusing on the attributes of individuals
or organizations, attention is drawn to the relationships among
social entities (examples of such relationships include friendship,
kinship, collaboration, strategic alliance and financial transfer).
While this shift in perspective has had profound theoretical
implications, it also has enabled the innovation of techniques
with vital and highly practical applications.
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Traditionally,
social network analysts have studied small groups, partly due
to the fact that the algorithms' computational requirements typically
are more intense than with traditional statistical techniques
- primarily because the number of observations to be considered
is the number of potential relationships (N*[N-1]) rather than
the number of individuals (N) in a study. With the advent of low-cost
computing power, however, it has become possible to analyze datasets
of relationships among hundreds or even thousands of individuals. |
