What are the local political, economic, and social conditions of the communities that sent insurrectionists to the U.S. Capitol in support of Donald Trump? Using a new dataset of the home counties of individuals charged for the Capitol Insurrection, we present the first systematic analysis of community-level factors on county rates of arrested insurrectionists. A one standard deviation decline in non-Hispanic White population share is associated with a 37% increase in the rate of insurrectionists, while manufacturing decline is associated with a 12% increase, even when controlling for population, racial makeup, and populist Trump support. The effect of white population decline is greater in counties whose U.S. Representative objected to the certification of the 2020 election results. Our findings suggest that improving economic conditions alone will not solve the problem of violent populism. Future research should further investigate the differences between electoral and violent populism. This dataset contains the Stata (version 18) dofiles and datafiles needed to replicate the figures and tables in the publication "The Political Geography of the January 6 Insurrectionists."

Terms of Access: By downloading the data, you agree to use the data only for academic research, agree not to share the data with outside parties, and agree not to attempt to re-identify individuals in the data set. We require this in order to protect the privacy of individuals in the data set and to comply with agreements made with TargetSmart. Abstract: We present the results of a large, $8.9 million campaign-wide field experiment, conducted among 2 million moderate and low-information “persuadable” voters in five battleground states during the 2020 US Presidential election. Treatment group subjects were exposed to an eight-month-long advertising program delivered via social media, designed to persuade people to vote against Donald Trump and for Joe Biden. We found no evidence the program increased or decreased turnout on average. We find evidence of differential turnout effects by modeled level of Trump support: the campaign increased voting among Biden leaners by 0.4 percentage points (SE: 0.2pp) and decreased voting among Trump leaners by 0.3 percentage points (SE: 0.3pp), for a difference-in-CATES of 0.7 points that is just distinguishable from zero (t(1035571) = −2.09, p = 0.036, DIC = 0.7 points, 95% CI = [−0.014, −0.00]). An important but exploratory finding is that the strongest differential effects appear in early voting data, which may inform future work on early campaigning in a post-COVID electoral environment. Our results indicate that differential mobilization effects of even large digital advertising campaigns in presidential elections are likely to be modest.

In this article, we hypothesize, and then demonstrate, that experiences of embarrassment have significantly increased in the United States, due in part, to the current situation in American politics under President Donald Trump. We provide support for our hypothesis by conducting both qualitative and quantitative analyses of Twitter posts in the U.S. obtained from the Crimson Hexagon database. Next, based on literature from social psychology, social neuroscience, and political theory, we propose a two-step process explaining why Trump's behavior has caused people in the U.S. to feel more embarrassment. First, compared to former representatives, Trump violates social norms in a manner that seems intentional, and second, these intentional norm violations specifically threaten the social integrity of in-group members—in this case, U.S. citizens. We discuss how these norm violations relate to the behavior of currently represented citizens and contextualize our rationale in recent changes of political representation and the public sphere. We conclude by proposing that more frequent, nation-wide experiences of embarrassment on behalf of the representative may motivate political actions to prevent further harm to individuals' self-concepts and protect social integrity.

Content

Antiquities Act

This folder contains the data behind the story Trump Might Be The First President To Scrap A National Monument.

This data was compiled by the National Parks Conservation Association and includes national monuments that were created by presidents by under the Antiquities Act. It does not include national monuments created by Congress.

Sources: National Parks Conservation Association and National Parks Service Archeology Program

Context

This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using GitHub's API and Kaggle's API.

This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.

Cover photo by Nick Tiemeyer on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Labor Force Participation Rate in the United States decreased to 62.30 percent in June from 62.40 percent in May of 2025. This dataset provides the latest reported value for - United States Labor Force Participation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This data package includes the underlying data files to replicate the data, tables, and charts presented in Why Trump’s tariff proposals would harm working Americans, PIIE Policy Brief 24-1.

If you use the data, please cite as: Clausing, Kimberly, and Mary E. Lovely. 2024. Why Trump’s tariff proposals would harm working Americans. PIIE Policy Brief 24-1. Washington, DC: Peterson Institute for International Economics.

Public opinion poll on: Congress; Economics; Elections; Ideology; Information; Middle East; Mood; Notable People; Political Partisanship; Presidency; Presidential Approval; Problems; Ratings; Religion; Terrorism; Values; Veterans; Vote for President; War.