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Title: Opinion dynamics on typical complex networks and applications
Author: Wang, W.
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2017
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This thesis investigates the dynamics in models of how opinions within a network of people, or of entities, change over time before arriving at a consensus. Considering the system as a complex network, continuous models are derived based on differential equations with each node in the network representing a person or entity. The interactions between the entities are explored and the influence of the topology of the network is established. It is shown that the structure and evolving mechanisms are crucial factors to determine whether there will be a stable consensus and to establish the network efficiency at which the system approaches a consensus. Both linear and nonlinear dynamics are considered. A new algorithm of a network partition is developed based on the fact that some nodes achieve local consensus earlier than the global stable solution. The experimental results show that the algorithm outperforms existing methods. Special consideration is given to networks which undergo an explosive phase transition, when a small number of new connections cause a rapid change in network dynamics with consensus occurring after the transition point. Results indicate that the consideration of spatial variations incorporating a social outcast strongly influence the dynamics approaching consensus. The methods are applied to illustrate the two party election competition, which demonstrates characteristic behaviour prior to majority.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available