In 2022, there were 161.42 million people registered to vote in the United States. This is a decrease from the previous election, when 168.31 million people were registered to vote.

Voting requirements

While voting laws differ from state to state, the basic requirements are the same across the entire country. People are allowed to vote in elections in the United States if they are a U.S. citizen, meet their state’s residency requirements, are at least 18 years old before Election Day, and are registered to vote before the registration deadline.

Vote early and often

Generally, younger people are not registered to vote at the same rate as older individuals. Additionally, young people tend not to vote as much as older people, particularly in midterm elections. However, in the 2016 presidential election, a significant number of people across all age groups voted in the election, resulting in a high voter turnout.

As of December 7, 2020, 66.7 percent of the eligible voting population in the United States voted in the 2020 presidential election. As of this date, voter turnout was highest in Minnesota, at 80 percent.

AP VoteCast is a survey of the American electorate conducted by NORC at the University of Chicago for Fox News, NPR, PBS NewsHour, Univision News, USA Today Network, The Wall Street Journal and The Associated Press.

AP VoteCast combines interviews with a random sample of registered voters drawn from state voter files with self-identified registered voters selected using nonprobability approaches. In general elections, it also includes interviews with self-identified registered voters conducted using NORC’s probability-based AmeriSpeak® panel, which is designed to be representative of the U.S. population.

Interviews are conducted in English and Spanish. Respondents may receive a small monetary incentive for completing the survey. Participants selected as part of the random sample can be contacted by phone and mail and can take the survey by phone or online. Participants selected as part of the nonprobability sample complete the survey online.

In the 2020 general election, the survey of 133,103 interviews with registered voters was conducted between Oct. 26 and Nov. 3, concluding as polls closed on Election Day. AP VoteCast delivered data about the presidential election in all 50 states as well as all Senate and governors’ races in 2020.

Using this Data - IMPORTANT

This is survey data and must be properly weighted during analysis: DO NOT REPORT THIS DATA AS RAW OR AGGREGATE NUMBERS!!

Instead, use statistical software such as R or SPSS to weight the data.

National Survey

The national AP VoteCast survey of voters and nonvoters in 2020 is based on the results of the 50 state-based surveys and a nationally representative survey of 4,141 registered voters conducted between Nov. 1 and Nov. 3 on the probability-based AmeriSpeak panel. It included 41,776 probability interviews completed online and via telephone, and 87,186 nonprobability interviews completed online. The margin of sampling error is plus or minus 0.4 percentage points for voters and 0.9 percentage points for nonvoters.

State Surveys

In 20 states in 2020, AP VoteCast is based on roughly 1,000 probability-based interviews conducted online and by phone, and roughly 3,000 nonprobability interviews conducted online. In these states, the margin of sampling error is about plus or minus 2.3 percentage points for voters and 5.5 percentage points for nonvoters.

In an additional 20 states, AP VoteCast is based on roughly 500 probability-based interviews conducted online and by phone, and roughly 2,000 nonprobability interviews conducted online. In these states, the margin of sampling error is about plus or minus 2.9 percentage points for voters and 6.9 percentage points for nonvoters.

In the remaining 10 states, AP VoteCast is based on about 1,000 nonprobability interviews conducted online. In these states, the margin of sampling error is about plus or minus 4.5 percentage points for voters and 11.0 percentage points for nonvoters.

Although there is no statistically agreed upon approach for calculating margins of error for nonprobability samples, these margins of error were estimated using a measure of uncertainty that incorporates the variability associated with the poll estimates, as well as the variability associated with the survey weights as a result of calibration. After calibration, the nonprobability sample yields approximately unbiased estimates.

As with all surveys, AP VoteCast is subject to multiple sources of error, including from sampling, question wording and order, and nonresponse.

Sampling Details

Probability-based Registered Voter Sample

In each of the 40 states in which AP VoteCast included a probability-based sample, NORC obtained a sample of registered voters from Catalist LLC’s registered voter database. This database includes demographic information, as well as addresses and phone numbers for registered voters, allowing potential respondents to be contacted via mail and telephone. The sample is stratified by state, partisanship, and a modeled likelihood to respond to the postcard based on factors such as age, race, gender, voting history, and census block group education. In addition, NORC attempted to match sampled records to a registered voter database maintained by L2, which provided additional phone numbers and demographic information.

Prior to dialing, all probability sample records were mailed a postcard inviting them to complete the survey either online using a unique PIN or via telephone by calling a toll-free number. Postcards were addressed by name to the sampled registered voter if that individual was under age 35; postcards were addressed to “registered voter” in all other cases. Telephone interviews were conducted with the adult that answered the phone following confirmation of registered voter status in the state.

Nonprobability Sample

Nonprobability participants include panelists from Dynata or Lucid, including members of its third-party panels. In addition, some registered voters were selected from the voter file, matched to email addresses by V12, and recruited via an email invitation to the survey. Digital fingerprint software and panel-level ID validation is used to prevent respondents from completing the AP VoteCast survey multiple times.

AmeriSpeak Sample

During the initial recruitment phase of the AmeriSpeak panel, randomly selected U.S. households were sampled with a known, non-zero probability of selection from the NORC National Sample Frame and then contacted by mail, email, telephone and field interviewers (face-to-face). The panel provides sample coverage of approximately 97% of the U.S. household population. Those excluded from the sample include people with P.O. Box-only addresses, some addresses not listed in the U.S. Postal Service Delivery Sequence File and some newly constructed dwellings. Registered voter status was confirmed in field for all sampled panelists.

Weighting Details

AP VoteCast employs a four-step weighting approach that combines the probability sample with the nonprobability sample and refines estimates at a subregional level within each state. In a general election, the 50 state surveys and the AmeriSpeak survey are weighted separately and then combined into a survey representative of voters in all 50 states.

State Surveys

First, weights are constructed separately for the probability sample (when available) and the nonprobability sample for each state survey. These weights are adjusted to population totals to correct for demographic imbalances in age, gender, education and race/ethnicity of the responding sample compared to the population of registered voters in each state. In 2020, the adjustment targets are derived from a combination of data from the U.S. Census Bureau’s November 2018 Current Population Survey Voting and Registration Supplement, Catalist’s voter file and the Census Bureau’s 2018 American Community Survey. Prior to adjusting to population totals, the probability-based registered voter list sample weights are adjusted for differential non-response related to factors such as availability of phone numbers, age, race and partisanship.

Second, all respondents receive a calibration weight. The calibration weight is designed to ensure the nonprobability sample is similar to the probability sample in regard to variables that are predictive of vote choice, such as partisanship or direction of the country, which cannot be fully captured through the prior demographic adjustments. The calibration benchmarks are based on regional level estimates from regression models that incorporate all probability and nonprobability cases nationwide.

Third, all respondents in each state are weighted to improve estimates for substate geographic regions. This weight combines the weighted probability (if available) and nonprobability samples, and then uses a small area model to improve the estimate within subregions of a state.

Fourth, the survey results are weighted to the actual vote count following the completion of the election. This weighting is done in 10–30 subregions within each state.

National Survey

In a general election, the national survey is weighted to combine the 50 state surveys with the nationwide AmeriSpeak survey. Each of the state surveys is weighted as described. The AmeriSpeak survey receives a nonresponse-adjusted weight that is then adjusted to national totals for registered voters that in 2020 were derived from the U.S. Census Bureau’s November 2018 Current Population Survey Voting and Registration Supplement, the Catalist voter file and the Census Bureau’s 2018 American Community Survey. The state surveys are further adjusted to represent their appropriate proportion of the registered voter population for the country and combined with the AmeriSpeak survey. After all votes are counted, the national data file is adjusted to match the national popular vote for president.

This data collection contains voter registration and turnout surveys. The files contain summaries at state, town, and county levels. Each level of data include: total population, total voting-age population, total voter registration (excluding ND, WI), total ballots cast, total votes cast for president, and voter registration by party. Note: see the documentation for information on missing data.

Dave Leip's website

The Dave Leip website here: https://uselectionatlas.org/BOTTOM/store_data.php lists the available data. Files are occasionally updated by Dave Leip, and new versions are made available, but CCSS is not notified. If you suspect the file you want may be updated, please get in touch with CCSS. These files were last updated on 9 JUL 2024.

Note that file version numbers are those assigned to them by Dave Leip's Election Atlas. Please refer to the Data and Reproduction Archive Version number in your citations for the full dataset.

For additional information on file layout, etc. see https://uselectionatlas.org/BOTTOM/DOWNLOAD/spread_turnout.html.

Similar data may be available at https://www.electproject.org/election-data/voter-turnout-data dating back to 1787.

As of late October 2024, young voter registration is lagging across a number of states when compared to the number registered on Election Day 2020. However, voter registration in swing states Michigan and Nevada increased by over ** percent among ** to 29-year-olds.

Since 1964, voter turnout rates in U.S. presidential elections have generally fluctuated across all age groups, falling to a national low in 1996, before rising again in the past two decades. Since 1988, there has been a direct correlation with voter participation and age, as people become more likely to vote as they get older. Participation among eligible voters under the age of 25 is the lowest of all age groups, and in the 1996 and 2000 elections, fewer than one third of eligible voters under the age of 25 participated, compared with more than two thirds of voters over 65 years.

In this paper, we revisit the effect of ballot access laws on voter confidence in the outcome of elections. We argue that voter confidence is conditioned by partisanship. Democrats and Republicans view election laws through a partisan lens, which is especially triggered when coalitions lose. We used The Integrity of Voting data set, along with other data sets, to test our hypotheses. The sample frame for the Integrity of Voting Survey was eligible persons who voted in the 2020 Presidential elections with accessible internet email addresses. Our sample consisted of two samples from two different vendors. Surveys were conducted with 17,526 voters drawing on two independent samples of registered voters who reported voting in the 2020 Presidential election. Email addresses for registered voters in each state were purchased from L2, a commercial vendor specializing in obtaining email addresses for registered voters. Interviews were solicited from one million voters in all 50 states, with 10,770 completed interviews for a response rate of .011%. A second sample of internet interviews were solicited and completed with 6,756 2020 voters using Dynata’s proprietary select-in survey of voters in selected states with smaller populations of registered voters. A minimum of roughly 100 2020 election voters were interviewed in each state. Our state samples were weighted using a raking technique on age, race, gender, education, and vote mode demographics from the U.S. Census Bureau’s 2020 Voting and Registration in the Election of November 2020 supplement to the Current Population survey (2021), as well as party identification totals from post-election exit polls conducted by the Associated Press (2020). Surveys were conducted between the first week in December, 2020 and the first week in February 2021.

In U.S. presidential elections since 1964, voter turnout among male and female voters has changed gradually but significantly, with women consistently voting at a higher rate than men since the 1980 election. 67 percent of eligible female voters took part in the 1964 election, compared to 72 percent of male voters. This difference has been reversed in recent elections, where the share of women who voted has been larger than the share of men by around four percent since 2004.

Throughout United States history, voter turnout among the voting eligible population has varied, ranging from below twelve percent in uncontested elections, to 83 percent in the 1876 election. In early years, turnout in presidential elections was relatively low, as the popular vote was not used in every state to decide who electors would vote for. When this was changed in the 1824 election, turnout increased dramatically, and generally fluctuated between seventy and eighty percent during the second half of the nineteenth century. Until the 1840 and 1842 elections, midterm elections also had a higher turnout rate than their corresponding presidential elections, although this trend has been reversed since these years.

Declining turnout in the twentieth century An increase in voting rights, particularly for black males in 1870 and for women in 1920, has meant that the share of the total population who are legally eligible to vote has increased significantly; yet, as the number of people eligible to vote increased, the turnout rate generally decreased. Following enfranchisement, it would take over fifty years before the female voter turnout would reach the same level as males, and over 150 years before black voters would have a similar turnout rate to whites. A large part of this was simply the lack of a voting tradition among these voter bases; however, the Supreme Court and lawmakers across several states (especially in the south) created obstacles for black voters and actively enforced policies and practices that disenfranchised black voter participation. These practices were in place from the end of the Reconstruction era (1876) until the the Voting Rights Act of 1965 legally removed and prohibited many of these obstacles; nonetheless, people of color continue to be disproportionally affected by voting restrictions to this day.

Recent decades In 1971, the Twenty-sixth Amendment lowered the minimum voting age in most states from 21 to 18 years old, which greatly contributed to the six and eight percent reductions in voter turnout in the 1972 and 1974 elections respectively, highlighting a distinct correlation between age and voter participation. Overall turnout remained below sixty percent from the 1970s until the 2004 election, and around forty percent in the corresponding midterms. In recent elections, increased political involvement among younger voters and those from ethnic minority backgrounds has seen these numbers rise, with turnout in the 2018 midterms reaching fifty percent. This was the highest midterm turnout in over one hundred years, leading many at the time to predict that the 2020 election would see one of the largest and most diverse voter turnouts in the past century, although these predictions then reversed with the arival of the coronavirus (COVID-19) pandemic. However, 2020 did prove to have the highest turnout in any presidential election since 1900; largely as a result of mail-in voting, improved access to early voting, and increased activism among grassroots organizations promoting voter registration.

The Voter Participation indicator presents voter turnout in Champaign County as a percentage, calculated using two different methods.

In the first method, the voter turnout percentage is calculated using the number of ballots cast compared to the total population in the county that is eligible to vote. In the second method, the voter turnout percentage is calculated using the number of ballots cast compared to the number of registered voters in the county.

Since both methods are in use by other agencies, and since there are real differences in the figures that both methods return, we have provided the voter participation rate for Champaign County using each method.

Voter participation is a solid illustration of a community’s engagement in the political process at the federal and state levels. One can infer a high level of political engagement from high voter participation rates.

The voter participation rate calculated using the total eligible population is consistently lower than the voter participation rate calculated using the number of registered voters, since the number of registered voters is smaller than the total eligible population.

There are consistent trends in both sets of data: the voter participation rate, no matter how it is calculated, shows large spikes in presidential election years (e.g., 2008, 2012, 2016, 2020) and smaller spikes in intermediary even years (e.g., 2010, 2014, 2018, 2022). The lowest levels of voter participation can be seen in odd years (e.g., 2015, 2017, 2019, 2021, 2023).

This data primarily comes from the election results resources on the Champaign County Clerk website. Election results resources from Champaign County include the number of ballots cast and the number of registered voters. The results are published frequently, following each election.

Data on the total eligible population for Champaign County was sourced from the U.S. Census Bureau, using American Community Survey (ACS) 1-Year Estimates for each year starting in 2005, when the American Community Survey was created. The estimates are released annually by the Census Bureau.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because this data is not available for Champaign County, the eligible voting population for 2020 is not included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes datasets on Population by Sex and Population Under 18 Years by Age.

Sources: Champaign County Clerk Historical Election Data; U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (10 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (5 October 2023).; Champaign County Clerk Historical Election Data; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (7 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (8 June 2021).; Champaign County Clerk Election History; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (13 May 2019).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (13 May 2019).; U.S. Census Bureau; American Community Survey, American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (6 March 2017).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey 2012 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).

Since 1824, when the popular vote was first used to determine the overall winner in U.S. presidential elections, the share of the population who participate in these elections has gradually increased. Despite this increase, participation has never reached half of the total population; partly due to the share of the population below the voting age of eighteen, but also as many potential voters above the age of eighteen do not take part, or are ineligible to vote. For example, in the 2016 election, approximately twenty million U.S. adults were ineligible to vote, while over 94 million simply did not participate; in this election, Donald Trump won the electoral college with 63 million votes, which means that 19.4 percent of the total U.S. population (or 27.3 percent of eligible voters) voted for the winning candidate. Development throughout history While the figures for the 2016 election may appear low, over 42 percent of the total population participated in this election, which was the third highest participation rate ever recorded (after the 2008 and 2020 elections). In the first election decided by a popular vote in 1824, only 350 thousand votes were cast from a total population of 10.6 million, although this increased to over four million votes by the 1856 election, as restrictions that applied to non-property holding white males were gradually lifted. Participation levels then dropped during the Civil War and Reconstruction era, as those who lived in Confederate states could not vote in 1864, and many white southerners were restricted or discouraged in the following election. Although universal suffrage was granted to black males in the wake of the Civil War, the majority of black Americans lived in the southern states, where lawmakers introduced Jim Crow laws in the late 1800s to suppress and disenfranchise the black vote, as well as poor white voters. The next major milestone was the introduction of women's suffrage in 1920, which saw voter participation increase by seven million votes (or seven percent) between the 1916 and 1920 elections. Between the 1910s and 1970s, the Great Migration saw many black Americans move away from the south to northern and western states, where they faced fewer obstacles when voting and greater economic mobility. This period of black migration began to decline in the 1960s and 1970s, during which time many Jim Crow laws were repealed in the south, through legislation such as the Voting Rights Act of 1965. Female participation also grew gradually, and has exceeded male voting participation in all elections since the 1980s. The minimum voting age was lowered from 21 to 18 in all states in 1971, although this seemingly had a minimal impact on the short-term trajectory of voter participation. Recent elections The 1992 election was the first in which more than one hundred million votes were cast, which was almost 41 percent of the total population. All elections since 2004 have also had more than one hundred million votes cast, which has again been more than forty percent of the total population. Another key factor in the increase in voter participation is the fact that people are living longer than ever before, and that those aged 65 and over have had the highest turnout levels since 1992. While some figures may be subject to change, the 2020 election set new records for voter turnout. Despite the global coronavirus pandemic, which many thought could cause the lowest turnout in decades, a record number of voters cast their ballots early or by mail, setting a new record of votes just shy of 160 million. In the 2020 election, Joe Biden and Donald Trump received 81.3 million and 74.2 million votes respectively, both beating Barack Obama's previous record of 69.3 million ballots in 2008. 2024 then saw a decline in the number of votes cast, with over three million fewer votes than in 2020.

This data set consists of all Fulton County Election results from April 2012 to present. Included with each record is the race, candidate, precinct, number of election day votes, number of absentee by mail votes, number of advance in person votes, number of provisional votes, total number of votes, name of election, and date of election. This data set is updated after each election.

As of *****************, former Vice President Joe Biden had won *** Electoral College votes in the race to become the next president of the United States, securing him the presidency. Candidates need *** votes to become the next president of the United States.

This map is specifically designed to provide a visual overview of the 2020 Yuma County election results for the presidential race as well as showcasing the current status of registered voters for 2024 along with their respective party affiliations.

David Leip provides election returns from presidential, senatorial, gubernatorial and House races at state, county and precinct level. Data includes names of candidates, parties, popular and electoral vote totals, voter turnout, and more. While some data is available for free on David Leip’s website, MIT researchers have access to more granular data from following elections and years: Presidential Primaries (county level): 2000, 2004, 2008, 2012, 2016, 2020 Presidential General Elections Results by: State: 1824-2012 County: 1980, 2016, 2020 Precincts: 1992, 1996, 2016, 2020 Congressional districts: 2016, 2020 House of Representatives (General Election, county level): 1992 – 2020 U.S. Senate (General Election, county level): 2020 Registration and Turnout (General Election , county level): 1992-2020

This is the dataset I used to figure out which sociodemographic factor including the current pandemic status of each state has the most significan impace on the result of the US Presidential election last year. I also included sentiment scores of tweets created from 2020-10-15 to 2020-11-02 as well, in order to figure out the effect of positive/negative emotion for each candidate - Donald Trump and Joe Biden - on the result of the election.

Details for each variable are as below: - state: name of each state in the United States, including District of Columbia - elec16, elec20: dummy variable indicating whether Trump gained the electoral votes of each state or not. If the electors casted their votes for Trump, the value is 1; otherwise the value is 0 - elecchange: dummy variable indicating whether each party flipped the result in 2020 compared to that of the 2016 - demvote16: the rate of votes that the Democrats, i.e. Hillary Clinton earned in the 2016 Presidential election - repvote16: the rate of votes that the Republicans , i.e. Donald Trump earned in the 2016 Presidential election - demvote20: the rate of votes that the Democrats, i.e. Joe Biden earned in the 2020 Presidential election - repvote20: the rate of votes that the Republicans , i.e. Donald Trump earned in the 2020 Presidential election - demvotedif: the difference between demvote20 and demvote16 - repvotedif: the difference between repvote20 and repvote16 - pop: the population of each state - cumulcases: the cumulative COVID-19 cases on the Election day - caseMar ~ caseOct: the cumulative COVID-19 cases during each month - Marper10k ~ Octper10k: the cumulative COVID-19 cases during each month per 10 thousands - unemp20: the unemployment rate of each state this year before the election - unempdif: the difference between the unemployment rate of the last year and that of this year - jan20unemp ~ oct20unemp: the unemployment rate of each month - cumulper10k: the cumulative COVID-19 cases on the Election day per 10 thousands - b_str_poscount_total: the total number of positive tweets on Biden measured by the SentiStrength - b_str_negcount_total: the total number of negative tweets on Biden measured by the SentiStrength - t_str_poscount_total: the total number of positive tweets on Trump measured by the SentiStrength - t_str_poscount_total: the total number of negative tweets on Trump measured by the SentiStrength - b_str_posprop_total: the proportion of positive tweets on Biden measured by the SentiStrength - b_str_negprop_total: the proportion of negative tweets on Biden measured by the SentiStrength - t_str_posprop_total: the proportion of positive tweets on Trump measured by the SentiStrength - t_str_negprop_total: the proportion of negative tweets on Trump measured by the SentiStrength - white: the proportion of white people - colored: the proportion of colored people - secondary: the proportion of people who has attained the secondary education - tertiary: the proportion of people who has attained the tertiary education - q3gdp20: GDP of the 3rd quarter 2020 - q3gdprate: the growth rate of the 3rd quarter 2020, compared to that of the same quarter last year - 3qsgdp20: GDP of 3 quarters 2020 - 3qsrate20: the growth rate of GDP compared to that of the 3 quarters last year - q3gdpdif: the difference in the level of GDP of the 3rd quarter compared to the last quarter - q3rate: the growth rate of the 3rd quarter compared to the last quarter - access: the proportion of households having the Internet access

As of November 23, 2020, over ***** million voters in the 2020 Presidential Election in the United States cast their votes before Election Day. Of these early votes, **** million were returned via mail-in ballots.

In the 1824 U.S presidential election, which was the first where a popular vote was used to determine the overall winner, approximately three percent of the U.S. population voted in the election, while only one percent actually voted for the winner. Over the following decades, restrictions that prevented non-property owning males from voting were gradually repealed, and almost all white men over the age of 21 could vote by the 1856 election. The next major development was the 15th Amendment to the U.S. Constitution following the American Civil War, which granted suffrage to all male citizens of voting age, regardless of race. Turnout then grew to almost twenty percent at the turn of the century, however Jim Crow laws played a large part in keeping these numbers lower than they potentially could have been, by disenfranchising black communities in the south and undoing much of the progress made during the Reconstruction Era. Extension of voting rights Female suffrage, granted to women in 1920, was responsible for the largest participation increase between any two elections in U.S. history. Between the 1916 and 1920 elections, overall turnout increased by almost seven percent, and it continued to grow to 38 percent by the 1940 election; largely due to the growth in female participation over time. Following a slight reduction during the Second World War and 1948 elections, turnout remained at between 36 and forty percent from the 1950s until the 1990s. Between these decades, the Voting Rights Act of 1965 and the Twenty-Sixth Amendment in 1971 respectively re-enfranchised many black voters in the south and reduced the voting age in all states from 21 to 18 years old. Participation among female voters has also exceeded male participation in all elections since 1980. Recent trends The 1992 election was the first where more than forty percent of the total population cast ballots, and turnout has been above forty percent in all presidential elections since 2004. Along with the extension of voting rights, the largest impact on voter turnout has been the increase in life expectancy throughout the centuries, almost doubling in the past 150 years. As the overall average age has risen, so too has the share of the total population who are eligible to vote, and older voters have had the highest turnout rates since the 1980s. Another factor is increased political involvement among ethnic minorities; while white voters have traditionally had the highest turnout rates in presidential elections, black voters turnout has exceeded the national average since 2008. Asian and Hispanic voter turnouts have also increased in the past twenty years, with the growing Hispanic vote in southern and border states expected to cause a major shift in U.S. politics in the coming decades.

In terms of the most popular presidents, in the 1940 election, Franklin D. Roosevelt became the first president to have been elected by more than one fifth of the total population. Three presidents were elected by more than 22 percent of the total population, respectively Lyndon B. Johnson in 1964, Richard Nixon in 1972 and Barack Obama in 2008, while Ronald Reagan's re-election in 1984 saw him become the only president in U.S. history to win with the support of more than 23 percent of the total population. While the vote count for the 2020 election is still to be finalized, President-elect Joe Biden has already received 81.28 million votes as of December 02, which would also translate to over 24.5 percent of the total population, and will likely near 25 percent by the end of the counting process.

Governments may have the capacity to flood social media with fake news, but little is known about the use of flooding by ordinary voters. In this work, we identify 2107 registered US voters that account for 80% of the fake news shared on Twitter during the 2020 US presidential election by an entire panel of 664,391 voters. We find that supersharers are important members of the network, reaching a sizable 5.2% of registered voters on the platform. Supersharers have a significant overrepresentation of women, older adults, and registered Republicans. Supersharers' massive volume does not seem automated but is rather generated through manual and persistent retweeting. These findings highlight a vulnerability of social media for democracy, where a small group of people distort the political reality for many. Methods This dataset contains aggregated information necessary to replicate the results reported in our work on Supersharers of Fake News on Twitter while respecting and preserving the privacy expectations of individuals included in the analysis. No individual-level data is provided as part of this dataset. The data collection process that enabled the creation of this dataset leveraged a large-scale panel of registered U.S. voters matched to Twitter accounts. We examined the activity of 664,391 panel members who were active on Twitter during the months of the 2020 U.S. presidential election (August to November 2020, inclusive), and identified a subset of 2,107 supersharers, which are the most prolific sharers of fake news in the panel that together account for 80% of fake news content shared on the platform. We rely on a source-level definition of fake news, that uses the manually-labeled list of fake news sites by Grinberg et al. 2019 and an updated list based on NewsGuard ratings (commercially available, but not provided as part of this dataset), although the results were robust to different operationalizations of fake news sources. We restrict the analysis to tweets with external links that were identified as political by a machine learning classifier that we trained and validated against human coders, similar to the approach used in prior work. We address our research questions by contrasting supersharers with three reference groups: people who are the most prolific sharers of non-fake political tweets (supersharers non-fake group; SS-NF), a group of average fake news sharers, and a random sample of panel members. In particular, we identify the distinct sociodemographic characteristics of supersharers using a series of multilevel regressions, examine their use of Twitter through existing tools and additional statistical analysis, and study supersharers' reach by examining the consumption patterns of voters that follow supersharers.

Approximately ***** million people were registered to vote in the presidential election scheduled in South Korea on June 3, 2025. The number of registered voters has slightly increased compared to the latest National Assembly elections, which took place in April 2024.