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LLM-powered ParlaCAP dataset analyzes European parliamentary agenda setting

Researchers have developed ParlaCAP, a new dataset designed to analyze parliamentary agenda setting across 28 European countries. This dataset utilizes a multilingual LLM in a teacher-student framework to create domain-specific policy topic classifiers, achieving annotation agreement comparable to human annotators. The ParlaCAP dataset includes extensive metadata and sentiment predictions, enabling comparative research on political attention and representation. AI

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IMPACT Enables new avenues for comparative political science research using LLM-based analysis of parliamentary data.

RANK_REASON This is a research paper introducing a new dataset and methodology for analyzing parliamentary discourse.

Read on arXiv cs.CL →

COVERAGE [1]

  1. arXiv cs.CL TIER_1 · Taja Kuzman Punger\v{s}ek, Peter Rupnik, Daniela \v{S}irini\'c, Nikola Ljube\v{s}i\'c ·

    Supercharging Agenda Setting Research: The ParlaCAP Dataset of 28 European Parliaments and a Scalable Multilingual LLM-Based Classification

    arXiv:2602.16516v2 Announce Type: replace Abstract: This paper introduces ParlaCAP, a large-scale dataset for analyzing parliamentary agenda setting across Europe, and proposes a cost-effective method for building domain-specific policy topic classifiers. Applying the Comparative…