Identifying influential actors in evolutionary complex networks

Program Code: 

Dr Alireza Abbasi (

Description of Work: 


The thorough understanding and modelling of the selection mechanisms in the evolution of networks can help to predict and manage the structural changes of the networks over time. This research aims to investigate quantitatively the network evolution processes during the evolution of real complex networks and also the behavioural attachment patterns of the actors who are affecting on the network changes. This requires the use of nature-inspired algorithms and techniques and further development of a theoretical framework for networks evolution and adaptation through the use of different multi-disciplinary theories. One of the important outputs of this study is to identify actors that facilitate the network evolution which has implication for decision makers and managers to control the way networks evolve.

Description of Work:

  • Understanding network dynamics and the structural factors driving the changes
  • Understanding the behaviours of actors which affects their link formation during the evolution of networks
  • Understanding the flow and diffusion of resources (information) over the network
  • Developing mathematical modelling and simulation techniques for extending the existing models of network dynamics and evolution
  • Evaluating the models against the existing methods and techniques