You Have the Floor: A Speaker-Aligned Corpus Derived from the Congressional Record

The United States Congressional Record serves as a comprehensive archive of legislative discourse, yet its sheer volume and unstructured format pose significant challenges for researchers interested in analyzing political language, speaker behavior, and ideological framing. This paper presents a new dataset that organizes Congressional speeches by individual speakers. Data was obtained using a mixture of the Congress.gov Application Programming Interface (API) and web-scraping techniques to retrieve the full text of the Congressional Record. After extracting roll-call votes and standardizing the transcripts to remove noisy artifacts and normalize formatting, each speaker is separated into individual files and annotated with metadata including name, political affiliation, years active, district or state represented, and professional social media accounts, if known. This enables fine-grained analysis of rhetorical patterns and linguistic strategies across different political groups as well as time periods. By making the dataset publicly available, we aim to support interdisciplinary research utilizing natural language processing (NLP).

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Publication Details

Journal
Proceedings of the International AAAI Conference on Web and Social Media
Published
2025-06-07
DOI
https://doi.org/10.1609/icwsm.v19i1.35941
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
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article

You Have the Floor: A Speaker-Aligned Corpus Derived from the Congressional Record

Jake Ryland Williams, Jennifer L Bochenek
Proceedings of the International AAAI Conference on Web and Social Media
Natural Language Processing Techniques
article

You Have the Floor: A Speaker-Aligned Corpus Derived from the Congressional Record

Jake Ryland Williams, Jennifer L Bochenek
article en

Abstract

The United States Congressional Record serves as a comprehensive archive of legislative discourse, yet its sheer volume and unstructured format pose significant challenges for researchers interested in analyzing political language, speaker behavior, and ideological framing. This paper presents a new dataset that organizes Congressional speeches by individual speakers. Data was obtained using a mixture of the Congress.gov Application Programming Interface (API) and web-scraping techniques to retrieve the full text of the Congressional Record. After extracting roll-call votes and standardizing the transcripts to remove noisy artifacts and normalize formatting, each speaker is separated into individual files and annotated with metadata including name, political affiliation, years active, district or state represented, and professional social media accounts, if known. This enables fine-grained analysis of rhetorical patterns and linguistic strategies across different political groups as well as time periods. By making the dataset publicly available, we aim to support interdisciplinary research utilizing natural language processing (NLP).

Proceedings of the International AAAI Conference on Web and Social MediaVol. 19
Drexel University (US)
Openalex Percentile: Top 94%
Natural Language Processing Techniques
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You Have the Floor: A Speaker-Aligned Corpus Derived from the Congressional Record — Jake Ryland Williams, Jennifer L Bochenek · Proceedings of the International AAAI Conference on Web and Social Media (2025) | TGRS Research Map | TGRS