ArticleScientific data2025
A text dataset of campaign speeches of the main tickets in the 2020 US presidential election.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- South Korean Election Campaign Booklet and Party Statements Corpora.Scientific data · 2025Article
- A text dataset of campaign speeches of the main tickets in the 2020 US presidential election.Scientific data · 2025Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.