Network Science and Party Politics

This is going to be a short post! Using network science, Carla Intal, my former MSc student and current co-author, and I showed (and quantified) the extent of Brexit-driven party distortion in the UK parliament and even predicted the individual MPs’ votes with staggering accuracy. Network science works! Carla has already won the Oxford Internet Institute Best Thesis Award for this work back in 2019, and today our paper after rounds of review, got finally published. Here is the paper abstract (which by the way is Open Access):

The British party system is known for its discipline and cohesion, but it remains wedged on one issue: European integration. We offer a methodology using social network analysis that considers the individual interactions of MPs in the voting process. Using public Parliamentary records, we scraped votes of individual MPs in the 57th parliament (June 2017 to April 2019), computed pairwise similarity scores and calculated rebellion metrics based on eigenvector centralities. Comparing the networks of Brexit- and non-Brexit divisions, our methodology was able to detect a significant difference in eurosceptic behaviour for the former, and using a rebellion metric we predicted how MPs would vote in a forthcoming Brexit deal with over 90% accuracy.

Published by Taha Yasseri

Associate Professor, School of Sociology, University College Dublin