A fundamental weakness of current sociological theory is that it does not relate micro level interactions to macro level patterns in any convincing way. Large-scale statistical, as well as qualitative, studies offer a good deal of insight into such macro phenomena as social mobility, community organization, and political structure. At the micro level, a large and increasing body of data and theory offers useful and illuminating ideas about what transpires within the confines of the small group. But how interaction in small groups aggregates to form large-scale patterns eludes us in most cases. I will argue in this paper that the analysis of processes in interpersonal networks provides the most fruitful micro-macro bridge. In one way or another, it is through these networks that small-scale interaction becomes translated into large-scale patterns and that these, in turn, feed back into small groups. Sociometry, the precursor of network analysis, has always been curiously peripheral—invisible, really—in sociological theory. This is partly because it has usually been studied and applied only as a branch of social psychology; it is also because of the inherent complexities of precise network analysis. We have had neither the theory nor the measurement and sampling techniques to move sociometry from the usual small-group level to that of larger structures. While a number of stimulating and suggestive studies have recently moved in this direction (Bott 1957; Mayer 1961; Milgram 1967; Boissevain 1968; Mitchell 1969), they do not treat structural issues in much theoretical detail. Studies which do so usually involve a level of technical complexity appropriate to such forbidding sources as the Bulletin of Mathematical Biophysics, where the original motivation for the study of networks was that of developing a theory of neural, rather than social, interaction (see the useful review of this literature by Coleman 1960; also Rapoport 1963). The strategy of the present paper is to choose a rather limited aspect of small-scale interaction—the strength of interpersonal ties—and to show, in some detail, how the use of network analysis can relate this aspect to such varied macro phenomena as diffusion, social mobility, political organization, and social cohesion in general.
Identification of important interacting proteins (IIPs) in Plasmodium falciparum using large-scale interaction network analysis and in-silico knock-out studies
