Evolutionary Dynamics of Complex Networks: Theory, Methods and Applications

We propose a new direction to understanding evolutionary dynamics of complex networks. We focus on two different types of collaboration networks—(i) academic collaboration networks (co-authorship); and, (ii) disaster collaboration networks. Some studies used collaboration networks to the existence of specific network topologies (structure) and preferential attachment as a structuring factor (Milojevi 2010). The academic co-authorship network represents a prototype of complex evolving networks (Barabási et al., 2002). Moreover, a disaster collaboration network presents a highly dynamic complex network, which evolves over time during the response and recovery phases of a disaster. We have chosen these two networks even though they are different in terms of complexity and domain but have common properties: open-based communication platform (self-organized system); geographically disperse actors (locational and cultural diversity of actors); autonomous behavior systems (non-hierarchy structure). The results show that the academic collaboration network has all the properties of small-world networks and can be considered a real small-world network with the result of its structural analysis maybe being extendable for other real-networks who share the common grounds of small-world properties. Our results further illustrate that the networks " clustering coefficients remain almost static over the evolution of both networks while the network is expanding over time through adding new actors and links to the networks.