coastalcph/populism-trump-chronos

Dataset Card

Dataset Summary

We curate and release an additional, much larger collection of 713 non-annotated speeches by Donald Trump, ranging over a decade from June 2015 to April 2025, dubbed TRUMP-CHRONOS, for a total of 656,136 sentences. This additional corpus is used to derive insights on the historical trends (2015-2025) of populist discourse in Donald Trump's campaign speeches. After consulting online sources to produce a complete list of Donald Trump rallies in this period, we sourced the transcripts of a subset of the speeches from UC Santa Barbara's American Presidency Project collection and used the publicly available version of OpenAI's Whisper to auto-transcribe the remainder by extracting audio from the videos of the speeches that we found on YouTube, C-SPAN and other online platforms. All transcripts were curated manually similarly to the TRUMP-2016 dataset and they reflect the actual speech addressed to the audience, rather than the prepared remarks that campaign managers routinely hand over to the press prior to or after a campaign event.

Our dataset excludes town hall events where Donald Trump exclusively responds to open-ended questions from the host or audience members. However, we include town halls that begin with an uninterrupted speech by Trump, omitting the subsequent Q&A portion from the transcript. We also exclude formal events (inauguration speeches, joint addresses to Congress, State of the Union addresses) and speeches where Trump is not addressing the public at large, (e.g., invitation-only events at think tanks, lobby groups, trade unions, galas, fund-raisers, or other civil society associations) since these are expected to focus on specific policy issues. However, we include speeches at GOP conventions (regional and national), and annual/semi-annual CPAC events because of their rally-like nature. The excluded speeches comprise a very small fraction of the overall roster of public events that Trump headlined.

Labeling / Annotation

The speeches in this set were split into separate sentences, which were automatically labeled based on the 3-class labeling using a fine-tuned RoBERTa classifier.

Related Task

The goal of this task is to develop a method to identify fine-grained forms of populist discourse. Under our working definition, populism has two main components: people-centrism and anti-elitism that need to operate in tandem before we can label a discursive body (e.g. a political speech or a social media post) as a populist one. To enable a fine-grained analysis of political content and take advantage of higher-frequency data for examining variations in populist discourse, we move beyond full speeches or paragraphs as units of analysis and instead focus on a lower-level discursive structure: the sentence. We frame the task as a three-way multi-label classification, where each sentence can be labeled as neutral, anti-elitist, or people-centric. The co-occurrence of the latter two labels indicates a fully populist sentence.

Statistics

NA

Data Fields

• speech_id: a string with the speech identifier.
• sentence: a string with a sentence from a speech.
• pop_code: an integer [0,1,2,3] identifying the category of the sentence.
• speaker: a string with the full name of the speaker.
• location: a string with the name of the location of the event.
• date: a string with the full date (YYYY-MM-DD) of the speech.

Data Instance / Example

{
'speech_id': '2016_03_01_trump.txt',
'sentence': 'Most importantly, we are going to take power back from the political class in Washington and return that power to you, the American people.',
'pop_code': 3,
'speaker': 'Donald Trump'
'location': 'Louisville, KY', 2016-03-01
'date': '2016-03-01',
}

How to use

from datasets import load_dataset
train_dataset = load_dataset('coastalcph/populism-trump-chronos', split='train')

Intended Usage

The dataset is intended for academic research for training and/or evaluating language models.

Discussion of Biases

The dataset includes speeches of Donald Trump from presidential campaign rallies. It may contain derogatory language against protected groups based on race, gender, or other characteristics. The authors do not endorse the use of such language.

Citation Information

Identifying Fine-grained Forms of Populism in Political Discourse: A Case Study on Donald Trump’s Presidential Campaigns. Ilias Chalkidis, Stephanie Brandl, and Paris Aslanidis. Arxiv Preprint, 2025.

@misc{chalkidis-et-al-2025-populism,
    title = "Identifying Fine-grained Forms of Populism in Political Discourse: A Case Study on Donald Trump’s Presidential Campaigns",
    author = "Chalkidis, Ilias and Brandl, Stephanie and Aslanidis, Paris",
    year = "2025",
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    url={https://arxiv.org/abs/2507.19303}
}