Tackling transparency in UK politics: application of large language models to clustering and classification of UK parliamentary divisions

Abstract

For a healthier democracy in the UK, novel methods of visualising political data are key to improving transparency, and encouraging engagement. The paper pro- poses a visualisation tool, using Large language models (LLMs), such as GPT3.5 and GPT4, to conduct Natural Language Processing (NLP) in a novel methodology. We investigate partisan voting profiles, specifically of the Conservative, Labour, and Liberal Democrat parties along 11 predetermined dimensions, rang- ing from Immigration & Borders, over Welfare & Social Housing, to European Union & Foreign Affairs. Higher order dimensions reveals shifts in party prefer- ence over time, while clear trends of more extreme voting behaviour can be seen across parties between 2016 - 2023. The novel visualisation methodology reveals that voting behaviour has become more polarised along party lines, with Labour becoming more left-wing and Conservatives becoming more right-wing regard- ing most political topics. Liberal Democrats voting behaviour has typically been those of an opposition party, albeit becoming somewhat more extreme.