Structure and Dynamics of Social Networks

Centre of Excellence in Computational Complex Systems Research



  1. Empirical studies on a large social network. We are currently analyzing a dataset related to the communications between a large number of people. Here, methods developed for characterizing weighted complex networks are being utilized. In particular, we are interested in the relationship of the strength of the social ties to the network structure, and its consequences on the function of the network.
  2. Modelling social network structures. Social networks can be characterized (among others) by the following: i) there is prominent community structure, i.e. the networks are organized into communities with dense internal links, ii) high-degree vertices (people with many social links) tend to be connected to other similar vertices, iii) average path lengths are short, iv) clustering is high. These salient features can be captured with relatively simple models of network growth. Future prospects include producing structures with realistic weight-topology correlations.
  3. Dynamic phenomena on social networks. The structural characteristics of social networks have effects on processes taking place on the networks, such as diffusion and spreading processes (e.g. information transmission, rumours). These processes can readily be investigated by computer simulations using real-world or simulated networks as lattices upon which the processes unfold.