CLCYSep 17, 2025

Framing Migration: A Computational Analysis of UK Parliamentary Discourse

Oxford
arXiv:2509.14197v11 citationsh-index: 12
Originality Synthesis-oriented
AI Analysis

This research provides insights into political discourse trends for policymakers and historians, though it is incremental in applying existing methods to new data.

The study analyzed migration discourse in UK parliamentary debates over 75 years, finding that UK attitudes remain relatively aligned across parties with a persistent ideological gap, while US discourse has grown increasingly polarized, and narrative frames shifted toward securitized topics like border control.

We present a large-scale computational analysis of migration-related discourse in UK parliamentary debates spanning over 75 years and compare it with US congressional discourse. Using open-weight LLMs, we annotate each statement with high-level stances toward migrants and track the net tone toward migrants across time and political parties. For the UK, we extend this with a semi-automated framework for extracting fine-grained narrative frames to capture nuances of migration discourse. Our findings show that, while US discourse has grown increasingly polarised, UK parliamentary attitudes remain relatively aligned across parties, with a persistent ideological gap between Labour and the Conservatives, reaching its most negative level in 2025. The analysis of narrative frames in the UK parliamentary statements reveals a shift toward securitised narratives such as border control and illegal immigration, while longer-term integration-oriented frames such as social integration have declined. Moreover, discussions of national law about immigration have been replaced over time by international law and human rights, revealing nuances in discourse trends. Taken together broadly, our findings demonstrate how LLMs can support scalable, fine-grained discourse analysis in political and historical contexts.

Foundations

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