The statistic shows the leading media sources used by adults to keep informed about political candidates and issues in the United States as of June 2018. The data shows that television was the most popular source of political information, with ** percent of surveyed voting U.S. adults saying that TV is what kept them informed about political issues during the election cycle. The second most used information source was TV news websites (including apps), and ** percent of respondents said that they used newspapers to keep up to date with political issues, double the share of U.S. voters who used online radio or podcasts.

Abstract: The Database on Ideology, Money in Politics, and Elections (DIME) is intended as a general resource for the study of campaign finance and ideology in American politics. The database was developed as part of the project on Ideology in the Political Marketplace, which is an on-going effort to perform a comprehensive ideological mapping of political elites, interest groups, and donors using the common-space CFscore scaling methodology (Bonica 2014). Constructing the database required a large-scale effort to compile, clean, and process data on contribution records, candidate characteristics, and election outcomes from various sources. The resulting database contains over 130 million political contributions made by individuals and organizations to local, state, and federal elections spanning a period from 1979 to 2014. A corresponding database of candidates and committees provides additional information on state and federal elections. The DIME+ data repository on congressional activity extends DIME to cover detailed data on legislative voting, lawmaking, and political rhetoric. (See http://dx.doi.org/10.7910/DVN/BO7WOW for details.) The DIME data is available for download as a standalone SQLite database. The SQLite database is stored on disk and can be accessed using a SQLite client or queried directly from R using the RSQLite package. SQLite is particularly well-suited for tasks that require searching through the database for specific individuals or contribution records. (Click here to download.) Overview: The database is intended to make data on campaign finance and elections (1) more centralized and accessible, (2) easier to work with, and (3) more versatile in terms of the types of questions that can be addressed. A list of the main value-added features of the database is below: Data processing: Names, addresses, and occupation and employer titles have been cleaned and standardized. Unique identifiers: Entity resolution techniques were used to assign unique identifiers for all individual and institutional donors included in the database. The contributor IDs make it possible to track giving by individuals across election cycles and levels of government. Geocoding: Each record has been geocoded and placed into congressional districts. The geocoding scheme relies on the contributor IDs to assign a complete set of consistent geo-coordinates to donors that report their full address in some records but not in others. This is accomplished by combining information on self-reported address across records. The geocoding scheme further takes into account donors with multiple addresses. Geocoding was performed using the Data Science Toolkit maintained by Pete Warden and hosted at http://www.datasciencetoolkit.org/. Shape files for congressional districts are from Census.gov (http://www.census.gov/rdo/data). Ideological measures: The common-space CFscores allow for direct distance comparisons of the ideal points of a wide range of political actors from state and federal politics spanning a 35 year period. In total, the database includes ideal point estimates for 70,871 candidates and 12,271 political committees as recipients and 14.7 million individuals and 1.7 million organizations as donors. Corresponding data on candidates, committees, and elections: The recipient database includes information on voting records, fundraising statistics, election outcomes, gender, and other candidate characteristics. All candidates are assigned unique identifiers that make it possible to track candidates if they campaign for different offices. The recipient IDs can also be used to match against the database of contribution records. The database also includes entries for PACs, super PACs, party committees, leadership PACs, 527s, state ballot campaigns, and other committees that engage in fundraising activities. Identifying sets of important political actors: Contribution records have been matched onto other publicly available databases of important political actors. Examples include: Fortune 500 directors and CEOs: (Data) (Paper) Federal court judges: (Data) (Paper} State supreme court justices: (Data) (Paper} Executives appointees to federal agencies: (Data) (Paper) Medical professionals: (Data) (Paper)

Welcome to BatchData, your trusted source for comprehensive US homeowner data, contact information, and demographic data, all designed to empower political campaigns. In the fast-paced world of politics, staying ahead and targeting the right audience is crucial for success.

At BatchData, we understand the importance of having the most accurate, up-to-date, and relevant data to help you make informed decisions and connect with your constituents effectively. With our robust data offerings, political campaign agencies can easily reach both homeowners and renters, using direct contact information such as cell phone numbers, emails, and mailing addresses.

The Power of Data in Political Campaigns In the digital age, political campaigns are increasingly reliant on data-driven strategies. Precise targeting, tailored messaging, and efficient outreach have become the cornerstones of successful political campaigning. BatchData equips political campaign agencies with the tools they need to harness the power of data in their campaigns, enabling them to make the most of every interaction. Harness the power of voter data and campaign & election data to effectively run political campaigns.

Key Features of BatchData 1. US Homeowner Data At BatchData, we understand that having access to accurate and comprehensive homeowner data is the bedrock of a successful political campaign. Our vast database includes information on homeowners across the United States, allowing you to precisely target this key demographic. With our homeowner data, you can segment your campaign and craft messages that resonate with this audience. Whether you're running a local, state, or national campaign, our homeowner data is an invaluable asset.

1. Contact Information 258M Phone Numbers (US Phone Number Data) BatchData doesn't just stop at providing you with demographic data; we go a step further by giving you direct contact information. We offer cell phone numbers, email addresses, and mailing addresses, ensuring that you can connect with your audience on multiple fronts. This multifaceted approach allows you to engage with potential voters in a way that suits their preferences and lifestyles. Whether you want to send targeted emails, reach out through phone calls, or even send physical mailers, BatchData has you covered with both the data and the tools. (See BatchDialer for more Info).

2. Demographic Data In addition to homeowner data and contact information, BatchData provides a treasure trove of demographic data. You can refine your campaign strategy by tailoring your messages to specific demographics, including age, gender, income, religious preferences, and more. Our demographic data helps you understand your audience better, allowing you to craft compelling messages that resonate with their values and interests.

3. Targeting Both Homeowners and Renters We understand that not all political campaigns are exclusively focused on homeowners. That's why BatchData caters to a diverse range of campaign needs. Whether your campaign is directed at homeowners or renters, our data sets have you covered. You can effectively target a broader spectrum of the population, ensuring that your message reaches the right people, regardless of their housing status.

Flexible Data Delivery Methods BatchData understands that political campaigns are time-sensitive, and efficiency is paramount. That's why we offer a variety of data delivery methods to suit your specific needs.

1. API Integration For real-time access to data, our API integration is your go-to solution. Easily integrate BatchData's data into your campaign management systems, ensuring that you always have the latest information at your fingertips.

2. Bulk File Delivery When you require a large volume of data in one go, our bulk file delivery option is ideal. We'll deliver the data to you in a format that's easy to import into your campaign databases, allowing you to work with a comprehensive dataset on your terms.

3. S3 Data Storage If you prefer to host your data in an S3 bucket, BatchData can seamlessly deliver your datasets to the cloud storage location of your choice. This option ensures that your data is readily available whenever you need it.

4. Self-Service List Building Our self-service list building tool empowers you to create custom lists based on your specific criteria. You have the flexibility to choose the data elements you need, ensuring that your campaign efforts are tailored to your goals.

5. File Exporting Need to download data for offline use or share it with your team? Our file exporting feature lets you export data in a user-friendly format, making it easy to work with.

6. On-Demand Concierge Services For those campaigns that require a more personalized touch, BatchData offers on-demand concierge services. Our experienced team is here to assist you in building lists, refining your targeting, and providing support as needed. This ...

This study investigated the cognitive processing of true and false political information. Specifically, it examined the impact of source credibility on the assessment of veracity when information comes from a polarizing source (Experiment 1), and effectiveness of explanations when they come from one's own political party or an opposition party (Experiment 2). These experiments were conducted prior to the 2016 Presidential election. Participants rated their belief in factual and incorrect statements that President Trump made on the campaign trail; facts were subsequently affirmed and misinformation retracted. Participants then re-rated their belief immediately or after a delay. Experiment 1 found that (i) if information was attributed to Trump, Republican supporters of Trump believed it more than if it was presented without attribution, whereas the opposite was true for Democrats and (ii) although Trump supporters reduced their belief in misinformation items following a correction, they did not change their voting preferences. Experiment 2 revealed that the explanation's source had relatively little impact, and belief updating was more influenced by perceived credibility of the individual initially purporting the information. These findings suggest that people use political figures as a heuristic to guide evaluation of what is true or false, yet do not necessarily insist on veracity as a prerequisite for supporting political candidates.

The main purpose of this data collection was to provide directly accessible information on change and stability of electoral behavior and political orientation in the Netherlands. This dataset is a compilation of common core variables included in the Dutch Parliamentary Election Studies of 1971, 1972, 1977, 1981, 1982, 1986, and 1989. However, several of the election studies consist of pre-election interviews as well as post-election interviews. Hence, the criteria for selecting the waves and variables were: (1) the waves and variables included in the integrated dataset should be as representative as possible of the Dutch electorate, (2) if a variable was not available in the first wave of a study, it was taken from the second wave or the third wave, (3) all variables included at least twice in the 1981, 1982, 1986, and 1989 studies were included in the integrated dataset, and (4) if necessary, selected variables were recoded and converted to facilitate longitudinal analyses. The major areas of study focus on national problems, political efficacy, perceived stand of the main political parties on important political issues, view of religion in society, satisfaction with government, social participation, voting behavior in recent elections, left-right self-rating, left-right rating of political parties, sense of civic competence, civic political participation, legitimacy of social protest and government reaction, political distrust, and political cynicism. Respondents' views on other salient political and social issues, such as abortion, nuclear energy, differences in income, and nuclear armaments, were also elicited.

POLITISKY24 (Political Stance Analysis on Bluesky for 2024) is a first-of-its-kind dataset for stance detection, focused on the 2024 U.S. presidential election. It designed for target-specific user-level stance detection and contains 16,044 user-target stance pairs centered on two key political figures, Kamala Harris and Donald Trump. In addition, this dataset includes detailed metadata, such as complete user posting histories and engagement graphs (likes, reposts, and quotes).

Stance labels were generated using a robust and evaluated pipeline that integrates state-of-the-art Information Retrieval (IR) techniques with Large Language Models (LLMs), offering confidence scores, reasoning explanations, and text spans for each label. With an LLM-assisted labeling accuracy of 81%, POLITISKY24 provides a rich resource for the target-specific stance detection task. This dataset enables the exploration of Bluesky platform, paving the way for deeper insights into political opinions and social discourse, and addressing gaps left by traditional datasets constrained by platform policies.

In the uploaded files:

• The file user_post_history_dataset.parquet includes the posting history of 8,561 active Bluesky users who have shared content related to American politics.

• The file user_post_list_for_stance_detection.parquet contains a list of up to 1,000 recent English-language post IDs per user, intended for use in the stance detection task.

• The file user_network_dataset.parquet captures users’ interactions through likes, reposts, and quotes.

• The file human_annotated_validation_user_stance_dataset.parquet contains human-annotated stance labels for 445 validation users toward Trump and Harris, resulting in a total of 890 user-target pairs. The labels are divided into three stances: 1 (favor), 2 (against), and 3 (neither).

• The file llm_annotated_validation_user_stance_dataset.parquet contains stance labels annotated by an LLM for the same 445 validation users toward Trump and Harris, also totaling 890 user-target pairs. In addition to stance labels, each pair includes an explanation of the reasoning, the source tweets, spans from the source tweets used in the reasoning, and a confidence score.

• The file llm_annotated_full_user_stance_dataset.parquet is similar to the above LLM-annotated validation file but covers all dataset users excluding the validation set. It provides stance labels for 8,022 users toward Trump and Harris, totaling 16,044 user-target pairs.

• The file human_annotated_validation_stance_relevancy_dataset (post-target entity pairs).parquet contains human-annotated stance labels for 175 validation posts toward Trump and Harris, resulting in 350 post-target pairs. The labels are divided into three stances: 1 (favor), 2 (against), and 3 (neither).

• The file human_annotated_validation_stance_relevancy_dataset (query-post stance relevancy pairs).parquet contains 700 query-post stance relevancy pairs derived from the post-target entity pairs.

Digital data from the political sphere is abundant, omnipresent, and more and more directly accessible through the Internet. Project Vote Smart (PVS) is a prominent example of this big public data and covers various aspects of U.S. politics in astonishing detail. Despite the vast potential of PVS’ data for political science, economics, and sociology, it is hardly used in empirical research. The systematic compilation of semi-structured data can be complicated and time consuming as the data format is not designed for conventional scientific research. This paper presents a new tool that makes the data easily accessible to a broad scientific community. We provide the software called pvsR as an add-on to the R programming environment for statistical computing. This open source interface (OSI) serves as a direct link between a statistical analysis and the large PVS database. The free and open code is expected to substantially reduce the cost of research with PVS’ new big public data in a vast variety of possible applications. We discuss its advantages vis-à-vis traditional methods of data generation as well as already existing interfaces. The validity of the library is documented based on an illustration involving female representation in local politics. In addition, pvsR facilitates the replication of research with PVS data at low costs, including the pre-processing of data. Similar OSIs are recommended for other big public databases.

The Database of Political Institutions presents institutional and electoral results data such as measures of checks and balances, tenure and stability of the government, identification of party affiliation and ideology, and fragmentation of opposition and government parties in the legislature, among others. The current version of the database, which is now hosted at the IDB, expands its coverage to about 180 countries for 40 years. Researchers at the World Bank Development Research Group first compiled the database in 2000 (see citation information below). It has become one of the most cited databases in comparative political economy and comparative political institutions. Almost 3,000 studies have used this database so far as a source of institutional and political data in their empirical analysis.

The Database of Political Institutions presents institutional and electoral results data such as measures of checks and balances, tenure and stability of the government, identification of party affiliation and ideology, and fragmentation of opposition and government parties in the legislature, among others. The current version of the database, which is now hosted at the IDB, expands its coverage to about 180 countries for 42 years, 1975–2017. Researchers at the World Bank Development Research Group first compiled the database in 2000 (see citation information below). It has become one of the most cited databases in comparative political economy and comparative political institutions. Almost 3000 studies have used this database so far as a source of institutional and political data in their empirical analysis.

This dataset contains compensation and expense summaries from monthly lobbying reports. Includes one record per client who paid compensation or incurred expenses during the filing period. Records for lobbyist firm expenses not reimbursed by clients are also included. Reports with no compensation or expenses have no records in this dataset.

This dataset is a best-effort by the PDC to provide a complete set of records as described herewith and may contain incomplete or incorrect information. The PDC provides access to the original reports for the purpose of record verification.

Data Coverage and Limitations: The data set covers that prior 16 years plus the current election year starting 2016. Pre-2016 records are available in the separate "Pre-2016 Lobbyist Compensation and Expenses by Source" dataset. This is a best-effort compilation that may contain incomplete or incorrect information. Original reports remain accessible for record verification.

Descriptions attached to this dataset do not constitute legal definitions; please consult RCW 42.17A and WAC Title 390 for legal definitions and additional information regarding political finance disclosure requirements.

CONDITION OF RELEASE: This publication constitutes a list of individuals prepared by the Washington State Public Disclosure Commission and may not be used for commercial purposes. This list is provided on the condition and with the understanding that the persons receiving it agree to this statutorily imposed limitation on its use. See RCW 42.56.070(9) and AGO 1975 No. 15.

Quantitative scholars in international relations often draw repeatedly on the same sources of country-year data across a diverse range of projects. The IPE Data Resource seeks to provide a public good to the field by standardizing and merging together variables from 89 IPE data sources into a single dataset, increasing efficiency and reducing the risk of data management errors. Easier access to data both encourages researchers to perform more robustness checks than they otherwise might and makes it easier for teachers of quantitative research methods to assign realistic exercises to their students. This resource will be updated and expanded annually and is available via the Harvard Dataverse Network.

This is an Active Citation data project. Active Citation is a precursor approach toAnnotation for Transparent Inquiry (ATI). It has now been converted to the ATI format. The annotated article can be viewed on the publisher's website. Project Summary This project develops and tests a new theory to explain left-right polarization in newer democracies, emphasizing the quality of governance and how it shapes incentives for radical parties to moderate. High-quality governance increases the relative salience of left-right programmatic appeals and makes coalitions with status quo parties attractive, creating centripetal incentives for radical parties and empowering moderate factions within those parties. Low-quality governance decreases the relative salience of left-right programmatic appeals and makes coalitions with status quo parties potentially poisonous, creating centrifugal incentives for radical parties and empowering extremist factions. The project employs a nested research design. Case studies of Venezuela and Brazil illustrate the mechanisms of the theory and evaluate its key propositions through process-tracing. These cases were selected because they capture significant variation on the dependent variable, because they are seen as particularly critical for understanding subjects such as the rise of the left in Latin America and the dynamics of programmatic polarization, and because they were the first three countries in the region where the left came to power. In the large-n portion of the research design, statistical analysis is utilized to assess the relationship between governance levels and left-right programmatic polarization across Latin America between 1994 and 2010. This relationship is substantively strong and robust to a variety of different modeling choices. Data Abstract The author primarily draws upon two original databases of qualitative materials collected for the project: a collection of roughly 500 “left party-related” sources (party documents, editorials and memoirs of left party leaders, etc.) and a compilation of roughly 900 news sources related to left parties and their factional conflicts. The data were collected from 2008 and 2013 and cover the period from 1985 and 2010. The “left party-related” sources were gathered through archives and libraries. A substantial archive of documents related to the Partido Dos Trabalhadores is housed at the Fundação Perseu Abramo, in Sao Paolo, Brazil. The University of Notre Dame acquired a microfilm copy of this entire archive (93 reels). The author examined the whole archive at Notre Dame, searching for documents and other information that bore directly on the concerns of the project. Because in Venezuela no central archive existed for the left parties involved, the author collated party-related documents and other information from diverse sources, mainly relatively rare books (usually published in Venezuela with small presses) that collected these documents. The database of news articles was generated in the following manner. For each country a newspaper or weekly magazine was selected that was known to provide in-depth political coverage from a relatively centrist perspective: El Universal in Venezuela and Folha de Sao Paulo in Brazil. The author then defined the time period for each case during which major factional conflicts within left parties occurred and were resolved: 1993-1998 in Venezuela and 1994-2002 in Brazil. The next step was to collect all stories from each news source in the defined time period that related to left parties, with an emphasis on their factional conflicts and its resolution. The process of doing so differed somewhat according to the medium in which the news source was available. Venezuela’s El Universal was only available on microfilm, requiring the author and a research assistant to review each daily issue, capturing stories to PDF according to defined criteria. Brazil’s Folha’s archives are available online, allowing its database to be searched by sets of key words, downloading the group of stories produced by these searches, and then including the individual stories in the database according to defined criteria. The interviews the author conducted as part of the broader project are not being shared at this time, but might be included in a planned second deposit to QDR of a larger stand-alone data collection. Files Description Each case study for which data are being shared contains a two-stage causal argument: (1) governance levels decisively affected factional dynamics within the major left party of that country; (2) the resolution of factional conflict bore strongly on the level of polarization in the emerging party system. For each case, each stage of this argument is supported by several pieces of diagnostic evidence original to the project – both party-related and news sources – that were either scanned (if available only in hard copy) or printed to PDF (if available on microfilm or the Web). The...

The January 2008 Political Survey, sponsored by the "https://www.pewresearch.org/" Target="_blank">Pew Research Center for the People and the Press, obtained telephone interviews with a nationally representative sample of 1,515 adults living in continental United States telephone households. The survey was conducted by Princeton Survey Research International. The interviews were conducted in English by Princeton Data Source, LLC from January 9-13, 2008. Statistical results are weighted to correct known demographic discrepancies. The margin of sampling error for the complete set of weighted data is +/-2.9 percent. Topics include politics, policy, economic conditions, election 2008, issue priorities, U.S. elections/voters and George W. Bush.

The statistic presents data from a survey on the most likely sources of fake news stories in the United States as of January 2017, sorted by political affiliation. During the survey, 39 percent of Republican respondents stated that they thought they would encounter fake news stories on CNN.

This dataset combines several existing datasets containing data on party organization, party performance, party positions and electoral systems into a single data source. These data a derive from different cross-national data collection projects. Some are online datasets, others were only printed in books. By integrating these datasets and providing unique party ids, we give comparative researchers a tool to investigate parties, their organizations and representation more thoroughly. The dataset contains data on 311 parties, from 22 countries, covering broadly the postwar period.

The Database of Political Institutions presents institutional and electoral results data such as measures of checks and balances, tenure and stability of the government, identification of party affiliation and ideology, and fragmentation of opposition and government parties in the legislature, among others. The current version of the database, which is now hosted at the IDB, expands its coverage to about 180 countries for 40 years, 1975-2015. Researchers at the World Bank Development Research Group first compiled the database in 2000 (see citation information below). It has become one of the most cited databases in comparative political economy and comparative political institutions. Almost 3000 studies have used this database so far as a source of institutional and political data in their empirical analysis.

This horizontal bar chart displays news by source using the aggregation count. The data is filtered where the keywords includes Sexual orientation-Political aspects-United States and the section is science.

The health and economic outcomes of the COVID-19 pandemic will in part be determined by how effectively experts can communicate information to the public and the degree to which people follow expert recommendation. Using a survey experiment conducted in May of 2020 with almost 5,000 respondents, this paper examines the effect of source cues and message frames on perceptions of information credibility in the context of COVID-19. Each health recommendation was framed by expert or non-expert sources, was fact- or experience-based, and suggested potential gain or loss to test if either the source cue or framing of issues affected responses to the pandemic. We find no evidence that either source cue or message framing influence people's responses—instead, respondents’ ideological predispositions, media consumption, and age explain much of the variation in survey responses, suggesting that public health messaging may face challenges from growing ideological cleavages in American politics.