A text dataset of campaign speeches of the main tickets in the 2020 US presidential election

Unstructured text data have gained popularity in political science, owing to advancements in rigorous 'text-as-data' methods that allow extracting insights into election outcomes, candidates' appeal to voters, ideologies and campaign strategies. Existing datasets on US presidential election campaign speeches are limited in size or source variation, and often contain speeches of different types (debates, rallies, official presidential events, e.g. inauguration), thus lacking consistency in their rhetorical content. The introduced dataset comprises the campaign speeches of the Democratic and Republican tickets for the 2020 US presidential election (1, 056 in total), covering the period between January 2019 and January 2021. Importantly, the dataset dictates specific criteria for the rhetorical structure of the speech ensuring consistency, critical for quantitative analysis. It has been carefully curated, yet only to the necessary extent to still be able to inform studies that require semantic or grammatical/syntactical structure. The provided corpus is hosted on Zenodo and GitHub under the CC BY-NC 4.0 license, and it aims to enhance timely studies on US presidential elections with high-quality text data.

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Publication Details

Journal
Scientific Data
Published
2025-04-19
DOI
https://doi.org/10.1038/s41597-025-04681-x
Citations
2
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
10.68

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article

A text dataset of campaign speeches of the main tickets in the 2020 US presidential election

Ioannis Chalkiadakis, Gareth W. Peters, Louise Anglès d’Auriac, Divina Frau-Meigs
2 citations
Scientific Data
Computational and Text Analysis Methods
10.68
article

A text dataset of campaign speeches of the main tickets in the 2020 US presidential election

Ioannis Chalkiadakis, Gareth W. Peters, Louise Anglès d’Auriac, Divina Frau-Meigs
article en
2 citations

Abstract

Unstructured text data have gained popularity in political science, owing to advancements in rigorous 'text-as-data' methods that allow extracting insights into election outcomes, candidates' appeal to voters, ideologies and campaign strategies. Existing datasets on US presidential election campaign speeches are limited in size or source variation, and often contain speeches of different types (debates, rallies, official presidential events, e.g. inauguration), thus lacking consistency in their rhetorical content. The introduced dataset comprises the campaign speeches of the Democratic and Republican tickets for the 2020 US presidential election (1, 056 in total), covering the period between January 2019 and January 2021. Importantly, the dataset dictates specific criteria for the rhetorical structure of the speech ensuring consistency, critical for quantitative analysis. It has been carefully curated, yet only to the necessary extent to still be able to inform studies that require semantic or grammatical/syntactical structure. The provided corpus is hosted on Zenodo and GitHub under the CC BY-NC 4.0 license, and it aims to enhance timely studies on US presidential elections with high-quality text data.

Scientific DataVol. 12(1)
Centre National de la Recherche Scientifique (FR), University of California, Santa Barbara (US), Institut Pasteur (FR), Université Sorbonne Nouvelle (FR)
University of California, Santa Barbara
Quality Education
Openalex Percentile: Top 2%
Computational and Text Analysis Methods
10.68
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A text dataset of campaign speeches of the main tickets in the 2020 US presidential election — Ioannis Chalkiadakis, Gareth W. Peters, et al. · Scientific Data (2025) | TGRS Research Map | TGRS