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Hierarchical visualisation of large social networks

Networks have been extensively used to capture social interactions, by representing individuals as nodes and their relationships as edges.Such networks have been used to model the spread of epidemics. A few nodes are 'infected', and over time they gradually infect their neighbours on the network, who in turn infect their neighbours, etc. This type of model can then be used to simulate different intervention strategies aimed at containing outbreaks.However, an important limitation is the difficulty to visualise these networks when …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

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