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Albert-Laszlo Barabási at the World Economic Forum 2012
CC BY-SA 2.0: By World Economic Forum from Cologny,
Switzerland - Mastering Complexity,
https://commons.wikimedia.org/w/index.php?curid=21275699
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Yet, the road to a fundamental and comprehensive understanding of networks is still rather rocky. (Barabási, 2005)Reference:
"Note 8. The first big difference between social and complex network analysis as a part of network science, however, is that the underlying data is not restricted to social systems but comprises all relationships between any kind of entities in any given complex system."
Summary of the differences between social network analysis and network science. Of course, this is a generalization and will not apply to every single network analytic project from either field.
"Note 9. A second important difference between network science and social network analysis is that (in general) the first induces micro-behavior from observed macro-behavior while (in general) the second predicts macro-behavior from hypothesized micro-behavior."
"Note 10. Social network analysis tries to capture many details from the social system of interest. Often, additional parameters of the persons under observation are requested and used for the analysis. The approach is thus a contextual approach that takes the context into account. In network science, the abstraction level is in most cases much higher and individual properties of the entities are much less often taken into account. The approach can be characterized as being largely context-free."
"Note 11. In summary (and a bit bold), social network analysis is a theory-driven, bottom-up approach that carefully models additional social information where available and takes it into account when interpreting the results. Network science follows a data-driven, top-down approach that tries to clean the data from all detail to compare the core structure of different complex networks."
