Dynamics of social complex networks: Some insights into recent research

Abstract

Social networks analysis (that is, the study of interactions among social actors from a structural viewpoint) has a long tradition covering several decades [1, 2, 3]. This sort of study has usually been performed over small social networks, and the limitation of size has conditioned the visibility of complexity [4, 5]. However, the situation has changed significantly in recent times due to basically two reasons. First, there is an increasing availability of larger social datasets (obtained in most cases from information and communication technologies). Secondly, a large number of physicists and other scholars from complexity science have started to take active interest in the field. New perspectives and tools have been provided by these ‘newcomers’, which in combination with the expertise and knowledge accumulated by ‘classical’ social network analysts, has formed the basis of a multidisciplinary field suitably termed the science of networks [6, 7]. This research has led to the formal definition of the complexity exhibited by social networks against the following simple ‘check list’ [5]. 1.The network must consist of a large number of nodes showing substantial heterogeneity. Here we understand heterogeneity to mean diversity of degree.2.Its structure has to present an ‘intricate architecture’, that is, a topology that cannot be expressed in terms of simple patterns (like ‘regular’ or ‘completely random’) but must include several degrees of freedom.3.This topological complexity is translated into the global system behavior in the form of ‘emergent phenomena’, i.e. even simple local interaction rules lead to a performance of the whole system that is richer than the sum of local effects.4.This influence of local feedbacks over the macroscopical behavior can be manifested, in particular, as nonlinearities in the operation of the processes that shape the network itself (i.e. sudden emergencies of determined structural features are observed when a certain external parameter exceeds a certain threshold value). Regarding the fulfillment of this list of requirements by social networks, Vega-Redondo refers to the results of previous studies about social structure to confirm that social networks satisfy the first two. Following the same reasoning, we notice that the other two requirements (covering dynamic aspects) are repeatedly recognized in social phenomena, for instance, collective behavior and social mobilization [8, 9] (third point), or the emergence of hierarchical social structures from interactions at an individual level [10, 11] (fourth point).