language:
- en
tags:
- legal
- finance
- climate
- social
pretty_name: 'CoCoHD: Congress Committee Hearing Dataset - Transcripts'
size_categories:
- 10K<n<100K
license: cc
Dataset Summary
The Congress Committee Hearing Dataset (CoCoHD) Transcripts comprises transcripts from congressional (House and Senate) hearings from 1997 to 2024.
This dataset is designed to facilitate research in natural language processing (NLP). It contains 30k+ U.S. congressional hearing transcripts from the 105th Congress to the 118th.
Dataset Structure
The hearing transcripts of each Congress session are kept in a folder and in text format.
Related Datasets
CoCoHD Hearing Details: This dataset provides comprehensive metadata for each congressional hearing, including information such as the hearing title, date, committee, and witnesses.
CoCoHD Hearing Details Cleaned: A refined version of the hearing details dataset, this collection has been processed to correct inconsistencies, standardize committee names, and remove duplicate or erroneous records, ensuring higher data quality for analysis.
These datasets offer valuable metadata that complements the CoCoHD transcripts, enabling more detailed and accurate analyses of congressional hearings.
Licensing
The CoCoHD Transcripts dataset is released under the CC BY-NC 4.0 license. This permits non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation
If you utilize this dataset in your research, please cite it as follows:
@inproceedings{hiray-etal-2024-cocohd,
title = "{C}o{C}o{HD}: Congress Committee Hearing Dataset",
author = "Hiray, Arnav and
Liu, Yunsong and
Song, Mingxiao and
Shah, Agam and
Chava, Sudheer",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-emnlp.911",
doi = "10.18653/v1/2024.findings-emnlp.911",
pages = "15529--15542",
abstract = "U.S. congressional hearings significantly influence the national economy and social fabric, impacting individual lives. Despite their importance, there is a lack of comprehensive datasets for analyzing these discourses. To address this, we propose the **Co**ngress **Co**mmittee **H**earing **D**ataset (CoCoHD), covering hearings from 1997 to 2024 across 86 committees, with 32,697 records. This dataset enables researchers to study policy language on critical issues like healthcare, LGBTQ+ rights, and climate justice. We demonstrate its potential with a case study on 1,000 energy-related sentences, analyzing the Energy and Commerce Committee{'}s stance on fossil fuel consumption. By fine-tuning pre-trained language models, we create energy-relevant measures for each hearing. Our market analysis shows that natural language analysis using CoCoHD can predict and highlight trends in the energy sector.",
}
GitHub Link
Contact Information
Please contact Agam Shah (ashah482[at]gatech[dot]edu) for any issues and questions.