Working Thesis Title
The role of network dimensionality in political polarisation.
Research on political polarisation typically focusses on finding a bimodal division between political parties, usually the US-American Republican and Democrat parties. This approach can be difficult to apply to many-party democracies like New Zealand. To address this gap, my thesis explores the idea that polarisation is instead about the political field narrowing down to two possible positions through a process of increasing correlation. As an interdisciplinary scholar, I also draw on work from political science which argues that polarisation is not just correlation in the political field, but is a process of dividing material and social networks as well, for example, through passing apartheid laws. To apply these frameworks to data science, I use Random Dot-Product Graphs to capture social networks in spaces such as Twitter, and use Singular Value Decomposition to assess whether their dimensionality how correlated the network is is changing. This method gives easily interpreted results about whether polarisation is occurring in the network.
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Supervisors:
Primary Supervisor:泭Giulio Dalla Riva
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