On June 24, 2022, the United States Supreme Court announced its decision to overturn Roe v. Wade, the 1973 decision that protected a woman's right to an abortion. A survey conducted shortly after found that approval for the decision was highest amongst Republicans, at 61 percent. Amongst those who identify as Democrats, only nine percent said they approve, and 75 percent said they disapprove.

The Digitalisation in Parties (DIGIPART) dataset (v.1) comprises information on party digitalisation features from 72 parties across five major European countries: Germany, Italy, France, Spain, and the United Kingdom. Compared to the initial version (v.0), which included data from 62 parties, version 1.1 of the DIGIPART dataset has been expanded to include new data on additional regional parties within these countries (n=76).

The dataset, stored in Excel format (xlsx) along with a codebook, captures information and evidence from various parties, collected and coded between July 2021 and September 2022.

Despite numerous studies examining the influence of digital technologies on political parties, a comprehensive comparative analysis of parties' responses to digitalisation remains scarce. The DIGIPART dataset aims to address this gap by mapping and analysing parties' digitalisation efforts.

DIGIPART includes fundamental data for identifying units of analysis, such as COUNTRY_ID and COUNTRY codes following Eurostat conventions, PARTY_ID codes, party acronyms, party names in English, year of foundation, ideology based on the Chapel Hill Experts Survey, election year, percentage of votes, and share of MPs in the national parliament's Lower Chamber. Vote and MP data are sourced from the Parlgov database or press sources for parties not covered in Parlgov.

Structured according to Fitzpatrick’s Five Pillar model, with adaptations for alternative digital democracy conceptions, the dataset provides insights into six main dimensions of party functions and activities: elections (EL), deliberation (DEL), participation (PART), resources (SOURCE), and communication (COM). Each dimension features several dichotomously coded indicators: 0 for no evidence of digital activity, 1 for evidence, and a dot (.) for controversial evidence or when none is found. Overall, the dataset offers specific information on 23 indicators, making it the most comprehensive account of party digitalisation to date.

With Abraham Lincoln's victory in the 1860 presidential election, the Republican Party cemented its position as one of the two major political parties in the United States. Since 1860, candidates from both parties have faced one another in 41 elections, with the Republican candidate winning 24 elections, to the Democrats' 17. The share of electoral college votes is often very different from the share of the popular vote received by each candidate in the elections, as the popular vote differences tend to be much smaller. Electoral college system In the U.S., the electoral college system is used to elect the president. For most states, this means that the most popular candidate in each state then receives that state's allocation of electoral votes (which is determined by the state's population). In the majority of elections, the margin of electoral votes has been over thirty percent between the two major party candidates, and there were even some cases where the winner received over ninety percent more electoral votes than the runner-up. Biggest winners The largest margins for the Republican Party occurred in the aftermath of the American Civil War, in the pre-Depression era of the 1920s, with Eisenhower after the Second World War, and then again with the Nixon, Reagan, and Bush campaigns in the 1970s and 80s. For the Democratic Party, the largest victories occurred during the First and Second World Wars, and for Lindon B. Johnson and Bill Clinton in the second half of the 20th century. In the past six elections, the results of the electoral college vote have been relatively close, compared with the preceding hundred years; George W. Bush's victories were by less than seven percent, Obama's victories were larger (by around thirty percent), and in the most recent elections involving Donald Trump he both won and lost by roughly 14 percent.

This dataset identifies and lists all the new parties emerged in Western Europe since 1945 and provides data about party system innovation, defined as the aggregate level of ‘newness’ recorded in a party system at a given election. Data are based on parliamentary elections (lower house) of 19 Western European countries since 1945. This dataset covers the entire universe of Western European elections held after World War II under democratic regimes. Data for Greece, Portugal and Spain have been collected after their democratizations in the 1970s. This dataset follows the recent publication of an article [Emanuele, V. and Chiaramonte, A. (2016), 'A growing impact of new parties: myth or reality? Party system innovation in Western Europe after 1945', Party Politics, Online First, DOI:10.1177/1354068816678887. http://ppq.sagepub.com/content/early/2016/11/17/1354068816678887.full] analysing new parties and party system innovation in Western Europe in Western Europe and based on this dataset.

The Elections Global dataset compiles information about election results to 1st or “lower” chambers in 207 countries from 1880 to 2015 including 3569 elections and 3282 parties. Cross-comparability of data on political parties is enhanced by harmonizing party names and codes via Party Facts (Döring and Regel 2019). The aim of Elections Global is to provide the most encompassing, consistent, harmonized and validated dataset about fundamental key variables of political research. What is more, Elections Global served as the base for V-Party, an expert survey on various aspects of party ideology and organizations conducted by the V-Dem Institute. Yet, Elections Global covers some smaller countries beyond V-Dem’s sample. If researchers are interested specifically in those cases, we suggest using Elections Global. Else, we recommend working with the extended and updated V-Party dataset.

As of November 2024, both of the major political parties in the United States were seen more unfavorably than favorably. Slightly more Americans saw the Republican Party in a more favorable light at ** percent, compared to the Democratic Party, ** percent.

Why do political parties present vague positions? We suggest that voter polarization provides them incentives to present either clear or vague positions, and the choice between these two is determined by the dimensionality of an issue for the parties. We find that facing voter polarization, Western European political parties present clearer positions on an issue when it is a first-dimension issue for them, but blur their positions when it is a secondary issue. Then, position blurring gives different implications to party systems with different degrees of issue dimensionality (e.g., American vs Western European party systems). The results also imply that political parties will respond to ongoing voter polarization on economic and immigration issues differently in the clarity of their position.

Replication data for the article Leader vs the Party Dilemma: The Case of a Party Rebirth in Czechiacvvm_filter.csv and okamura_cvvm.csv contain survey data used for the analysis of electoral behaviour.PSRK13_21.xlsx contains the results of preferential voting for the Czech Parliamentary elections in 2013 and 2021

Scholars, the media, and ordinary people alike express alarm at the apparent loathing between Democrats and Republicans in the mass public. However, the evidence of such loathing typically comes from survey items that measure attitudes toward the Democratic and Republican Parties, rather than attitudes toward ordinary partisans. Using a nationally representative survey, I find that Democrats and Republicans have substantially more positive feelings toward ordinary people belonging to the opposing party than they do toward politicians in the opposing party and the opposing party itself. These results indicate that research relying on measures of feelings toward the opposing “Party” vastly overstates levels of partisan animosity in the American public, and demonstrate the need to distinguish between attitudes toward party elites and ordinary partisans in future research.

Electoral systems determine the role that representatives’ party affiliations play in political representation. According to conventional expectations, party affiliation drives the behavior of representatives when they are elected under a proportional system, while majoritarian systems mute the role of party affiliation by forcing politicians to converge to the median position of their constituency. This study directly tests these predictions within a common party system by matching referenda decisions of constituents with voting behavior of their representatives who are elected either under a majoritarian or proportional system.

Despite numerous studies examining the influence of digital technologies on political parties, a comprehensive comparative analysis of parties' responses to digitalisation remains scarce. The DIGIPART dataset aims to address this gap by mapping parties' digitalisation.

The Digitalisation in Parties (DIGIPART) dataset (v.1) comprises information on party digitalisation features from 72 parties across five major European countries: Germany, Italy, France, Spain, and the United Kingdom. Compared to the initial version (v.0), which included data from 62 parties, version 1.1 of the DIGIPART dataset has been expanded to include new data on additional regional parties within these countries (n=76).

The dataset, stored in Excel format (xlsx) along with a codebook, captures information and evidence from various parties, collected and coded between July 2021 and September 2022.

DIGIPART includes fundamental data for identifying units of analysis, such as COUNTRY_ID and COUNTRY codes following Eurostat conventions, PARTY_ID codes, party acronyms, party names in English, year of foundation, ideology based on the Chapel Hill Experts Survey, election year, percentage of votes, and share of MPs in the national parliament's Lower Chamber. Vote and MP data are sourced from the Parlgov database or press sources for parties not covered in Parlgov.

Structured according to Fitzpatrick’s Five Pillar model, with adaptations for alternative digital democracy conceptions, the dataset provides insights into six main dimensions of party functions and activities: elections (EL), deliberation (DEL), participation (PART), resources (SOURCE), and communication (COM). Each dimension features several dichotomously coded indicators: 0 for no evidence of digital activity, 1 for evidence, and a dot (.) for controversial evidence or when none is found. Overall, the dataset offers specific information on 23 indicators, making it the most comprehensive account of party digitalisation to date.

Version 1.2 (submitted on 12/10/2024) includes an updated version of the codebook.

According to a 2023 survey, Americans between 18 and 29 years of age were more likely to identify with the Democratic Party than any other surveyed age group. While 39 percent identified as Democrats, only 14 percent identified ad Republicans. However, those 50 and older identified more with the Republican Party.

In October 2012, the LISS panel was presented a questionnaire to research the extent to which differences between men and women in radical right voting can be explained through characteristics of radical right parties.

To answer the research question, eight campaign videos were made, played by actors representing political candidates. Households were assigned a video at random. In the videos, the following elements were manipulated:

1. center-right or radical right message
2. aggressive or nuanced manner of speech
3. male or female actor

In addition, a random selection of half the households was explicitly told that the party shown in the video was a radical-right party.

Values in parenthesis indicate the corresponding standard error of the means. Last column indicates the outcome of a paired t-test (n = 50) for significant difference between the mean values of party and Wikipedia boxes within the supporters of the two parties.

In the last few decades, the Democratic Party has often pulled ahead of the Republican Party in terms of party identification. However, 2022 saw a shift in party identification, with slightly more Americans identifying with the Republican Party for the first time since 2011, when both parties stood at ** percent in 2011. These values include not only those surveyed who identified with a major political party, but also those who identified as independent, but have leanings towards one party over another.

Regression of determinants predicting the size of the difference between the perceived effect of online targeted political advertisement on the other party versus one’s own party.

There are two datasets within the zip file.The experimental design of study1 was a 2(group: human vs AI)*6 (unfairness: 100:0, 90:10, 80:20, 70:30, 60:40, 50:50) design, with group as the between-subjects variable, unfairness as the within-subjects variable, and third-party punishment (TP) as the dependent variable. For easier understanding of the results, we combined the six levels of unfairness into three levels: 100-0, 90-10 allocation defined as high unfairness situations (corresponding to TP_high), and 80-20, 70-30 allocation combinations as median unfairness situations (corresponding to TP_median), and the 60-40, 50-50 allocation were defined as low unfairness situations (corresponding to TP_low). In addition gender, age, education level were collected as control variables.The experimental design of study2 was identical to study1, with the addition of TPoutrage_low, TPoutrage_median, and TPoutrage_high as the scores of the mediating variable moral outrage in the three unfairness situations. Responsibility attribution (TPFAE) scores were also measured, calculated from TPFAE_in-TPFAE_ex.

This dataset provides data on electoral volatility and its internal components in parliamentary elections (lower house) of 19 Western European countries for the 1945-2015 period. It covers the entire universe of Western European elections held after World War II under democratic regimes. Data for Greece, Portugal and Spain have been collected after their democratizations in the 1970s. Altogether, a total of 339 elections (or, more precisely, electoral periods) are included. This dataset follows the recent publication of an article [Chiaramonte, A. and Emanuele, V. (2015), Party System Volatility, Regeneration and De-Institutionalization in Western Europe (1945-2015), Party Politics, doi:10.1177/1354068815601330 http://ppq.sagepub.com/content/early/2015/08/24/1354068815601330.abstract] tackling the issue of party system (de-)institutionalization in Western Europe and based on this dataset.

Parliament is a core institution to the political power structure. Parties and parliamentarians are responsible for expressing and translating the interests of "the people" in the legislature. Social groups with limited party representation in parliament are politically unequal to social groups with greater representation. Yet, scholars lack information to address research questions about how well social groups are represented in parliament across nations and time.The dataset “Party Representation of Social Groups” (PaReSoGo) contains a replicable and straightforward measure of the party representation of social groups per country and year from high-quality publicly available survey and administrative data. For survey data, we use the European Social Survey (ESS) 2002 - 2016 that contains items on sociodemographics, social attitudes, and retrospective vote choice, i.e. the party that the respondents said they voted for in the last general election. We aggregate the ESS items to the country and year level and match that distribution with the ParlGov data on the percentage of parliamentarians in each party in parliament per country and year. Our country-year measure is based on the idea of issue congruence measures that match distributions. In our data, this match is made via the Dissimilarity Index (DI). Here, the DI is a measure of distance in party representation between gender, age, education, intersectional, and attitudinal groups’ retrospective party vote choices and the distribution of parliamentarians in parties. This archived version of PaReSoGo contains 150 "straightforward" country years, which cover eight ESS rounds (2002-2016) and 95 national elections (1999-2016) across 25 countries: Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Greece, Iceland, Ireland, Israel, Luxembourg, the Netherlands, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, and the United Kingdom. We also archive 51 country years which we consider “complicated”, marked accordingly, including countries with complex electoral systems, when the survey data available and the final seat distribution in parliament cannot be directly compared, or in case of survey fieldwork problems.For each country-year, we calculated the DI for all ESS respondents and selected social groups, including gender, age, education, intersections of gender and age, and attitudinal groups. Additionally, we calculated an election-to-fieldwork time distance and provided information on a card being shown in the ESS.The archived data package consists of a summary table in .xls and .csv formats, the codebook, .xls files with raw calculations for each of the 150 "straightforward" country-years and accompanying .do files with the Stata code. We also include the summary table (.xls and .csv), DI calculations (.xls) and the code (.do) for the 51 “complicated” country-years. The codebook contains the data basics, the description of the methodology and of all variables, and detailed notes on DI calculations for every country, including an explanation of the complicated merges of the ESS and the ParlGov lists and the details on the electoral system in the country.Suggested citation:Zelinska, Olga and Joshua K. Dubrow. 2021. Party Representation of Social Groups (PaReSoGo) v.1.0. Institute of Philosophy and Sociology of the Polish Academy of Sciences, funded by National Science Centre, Poland 2016/23/B/HS6/03916. Polish Social Data Archive.

For each data type, we list the raw data variables used and any measures constructed from those data.