Why social networks are different from other types of networks

Physical Review E - Statistical, Nonlinear, and Soft Matter Physics

Volumn 68, Issue 3 2, 2003, Pages 361221-3612218

  Newman, M E J ^a   Park, Juyong ^b  

^a UNIVERSITY OF MICHIGAN   (United States)

^b SANTA FE INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION METHODS; PHYSIOLOGY; REAL TIME SYSTEMS; SOCIAL ASPECTS;

SOCIAL NETWORKS;

INTERNET;

EID: 0242663598     PISSN: 1063651X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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41. An alternative theory is that individuals introduce pairs of their acquaintances to one another, thus completing network triangles and increasing the clustering coefficient. Several models of this "triadic closure" process have been studied in the literature [35-40].
42. Since our model requires all connected pairs of individuals to belong to at least one common group, we define the groups to include both the core members shown by the colors in Fig. 2 and all individuals connected directly to those core members. This makes the group memberships overlap, as they do in the model.
43. We deliberately chose to define the groups in our calculation using an algorithmic method - the method of Ref. [29] - to avoid possible subjective biases in the calculation. Some might argue however that, for a network such as this, group membership could be better assigned by a knowledgable human experimenter. We have performed calculations in this way also, assigning groups according to the authors' personal knowledge of the field. This results in somewhat different group assignments, though not grossly so, and a slightly higher value for p of 0.178. The final value of r extracted from the model is however unchanged within errors, at r = 0.183. Thus, the agreement between empirical observation and model is again good.