[Submitted on 30 Jul 2026]
Title:Discourse Analysis of Legislative Bill Discussions
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Abstract:Legislative hearings are distinct communication events with their own human recognizable structure and logic, yet they have been analyzed as distinct phenomena beyond their transcripts. Understanding legislative hearings at a deeper level is a major step in analyzing the work and power relationships within democratic bodies. In this work, we present a novel end-to-end pipeline for parsing rhetorical structures from legislative committee hearings with the goal of improving legislative discourse analysis and democratic accountability. We also propose a rhetorical structure grammar and find that 55.21% of California state bill discussions in our dataset can be parsed with this grammar. We evaluate our pipeline with two utterance section classifiers on a random subset of over 2,000 annotated utterances corresponding to 100 hearings. We find that a logistic regression-based classifier with grammar-based output masking and utterance tag smoothing outperforms more complex models, achieving an F1 score of 52.8% against our ground truth discourse section labels.
Comments: 10 pages, 4 figures
Subjects:
Computation and Language (cs.CL)
Cite as: arXiv:2611.05381 [cs.CL]
(or arXiv:2611.05381v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2611.05381
arXiv-issued DOI via DataCite
Submission history
From: Isaac Rudnick [view email] [v1] Thu, 30 Jul 2026 00:13:23 UTC (1,193 KB)
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