Stability in Flux: Group Dynamics in Evolving Networks

From Facebook groups and online gaming clans, to social movements and terrorist cells, groups of individuals aligned by interest, values or background are of increasing interest to social network researchers (Snow et al., 1980; Zheleva et al., 2009). In particular, understanding the structural and dynamic factors that influence the evolution of these groups remains an open challenge (Palla et al., 2007; Geard and Bullock, 2008, 2010). Why do some groups persist and succeed, while others fail to do so? Three features characterise real social networks. They are inherently dynamic: explaining the structure of social networks requires us to understand how this structure is created, modified and maintained. They are co-evolutionary, exhibiting a reflexive relationship between topology and state. For example, individuals often interact preferentially with others who are similar to themselves, thus state affects topology; at the same time, neighbouring individuals tend to influence one another and hence become more similar, thus topology affects state (Gross and Blasius, 2008). Finally, interactions between individuals are not distributed uniformly across a network: rather, we can detect community structure, in which subsets of individuals are more densely linked to each other than to the rest of the population (Newman, 2006). Analysis of telephone and collaboration data by Palla et al. (2007) has demonstrated some of the ways in which social groups evolve over time, but there is more to be done in understanding the multi-level relationship between individua