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.

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 Over the following decades, restrictions that prevented non-property owning males from voting were gradually repealed, and almost all white men over the age of 21 could vote by the 1856 election.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.

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.

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.

PROBLEM AND OPPORTUNITY In the United States, voting is largely a private matter. A registered voter is given a randomized ballot form or machine to prevent linkage between their voting choices and their identity. This disconnect supports confidence in the election process, but it provides obstacles to an election's analysis. A common solution is to field exit polls, interviewing voters immediately after leaving their polling location. This method is rife with bias, however, and functionally limited in direct demographics data collected. For the 2020 general election, though, most states published their election results for each voting location. These publications were additionally supported by the geographical areas assigned to each location, the voting precincts. As a result, geographic processing can now be applied to project precinct election results onto Census block groups. While precinct have few demographic traits directly, their geographies have characteristics that make them projectable onto U.S. Census geographies. Both state voting precincts and U.S. Census block groups: are exclusive, and do not overlap are adjacent, fully covering their corresponding state and potentially county have roughly the same size in area, population and voter presence Analytically, a projection of local demographics does not allow conclusions about voters themselves. However, the dataset does allow statements related to the geographies that yield voting behavior. One could say, for example, that an area dominated by a particular voting pattern would have mean traits of age, race, income or household structure. The dataset that results from this programming provides voting results allocated by Census block groups. The block group identifier can be joined to Census Decennial and American Community Survey demographic estimates. DATA SOURCES The state election results and geographies have been compiled by Voting and Election Science team on Harvard's dataverse. State voting precincts lie within state and county boundaries. The Census Bureau, on the other hand, publishes its estimates across a variety of geographic definitions including a hierarchy of states, counties, census tracts and block groups. Their definitions can be found here. The geometric shapefiles for each block group are available here. The lowest level of this geography changes often and can obsolesce before the next census survey (Decennial or American Community Survey programs). The second to lowest census level, block groups, have the benefit of both granularity and stability however. The 2020 Decennial survey details US demographics into 217,740 block groups with between a few hundred and a few thousand people. Dataset Structure The dataset's columns include: Column Definition BLOCKGROUP_GEOID 12 digit primary key. Census GEOID of the block group row. This code concatenates: 2 digit state 3 digit county within state 6 digit Census Tract identifier 1 digit Census Block Group identifier within tract STATE State abbreviation, redundent with 2 digit state FIPS code above REP Votes for Republican party candidate for president DEM Votes for Democratic party candidate for president LIB Votes for Libertarian party candidate for president OTH Votes for presidential candidates other than Republican, Democratic or Libertarian AREA square kilometers of area associated with this block group GAP total area of the block group, net of area attributed to voting precincts PRECINCTS Number of voting precincts that intersect this block group ASSUMPTIONS, NOTES AND CONCERNS: Votes are attributed based upon the proportion of the precinct's area that intersects the corresponding block group. Alternative methods are left to the analyst's initiative. 50 states and the District of Columbia are in scope as those U.S. possessions voting in the general election for the U.S. Presidency. Three states did not report their results at the precinct level: South Dakota, Kentucky and West Virginia. A dummy block group is added for each of these states to maintain national totals. These states represent 2.1% of all votes cast. Counties are commonly coded using FIPS codes. However, each election result file may have the county field named differently. Also, three states do not share county definitions - Delaware, Massachusetts, Alaska and the District of Columbia. Block groups may be used to capture geographies that do not have population like bodies of water. As a result, block groups without intersection voting precincts are not uncommon. In the U.S., elections are administered at a state level with the Federal Elections Commission compiling state totals against the Electoral College weights. The states have liberty, though, to define and change their own voting precincts https://en.wikipedia.org/wiki/Electoral_precinct. The Census Bureau practices "data suppression", filtering some block groups from demographic publication because they do not meet a population threshold. This practice...

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.

This web map displays data from the voter registration database as the percent of registered voters by census tract in King County, Washington. The data for this web map is compiled from King County Elections voter registration data for the years 2013-2019. The total number of registered voters is based on the geo-location of the voter's registered address at the time of the general election for each year. The eligible voting population, age 18 and over, is based on the estimated population increase from the US Census Bureau and the Washington Office of Financial Management and was calculated as a projected 6 percent population increase for the years 2010-2013, 7 percent population increase for the years 2010-2014, 9 percent population increase for the years 2010-2015, 11 percent population increase for the years 2010-2016 & 2017, 14 percent population increase for the years 2010-2018 and 17 percent population increase for the years 2010-2019. The total population 18 and over in 2010 was 1,517,747 in King County, Washington. The percentage of registered voters represents the number of people who are registered to vote as compared to the eligible voting population, age 18 and over. The voter registration data by census tract was grouped into six percentage range estimates: 50% or below, 51-60%, 61-70%, 71-80%, 81-90% and 91% or above with an overall 84 percent registration rate. In the map the lighter colors represent a relatively low percentage range of voter registration and the darker colors represent a relatively high percentage range of voter registration. PDF maps of these data can be viewed at King County Elections downloadable voter registration maps. The 2019 General Election Voter Turnout layer is voter turnout data by historical precinct boundaries for the corresponding year. The data is grouped into six percentage ranges: 0-30%, 31-40%, 41-50% 51-60%, 61-70%, and 71-100%. The lighter colors represent lower turnout and the darker colors represent higher turnout. The King County Demographics Layer is census data for language, income, poverty, race and ethnicity at the census tract level and is based on the 2010-2014 American Community Survey 5 year Average provided by the United States Census Bureau. Since the data is based on a survey, they are considered to be estimates and should be used with that understanding. The demographic data sets were developed and are maintained by King County Staff to support the King County Equity and Social Justice program. Other data for this map is located in the King County GIS Spatial Data Catalog, where data is managed by the King County GIS Center, a multi-department enterprise GIS in King County, Washington. King County has nearly 1.3 million registered voters and is the largest jurisdiction in the United States to conduct all elections by mail. In the map you can view the percent of registered voters by census tract, compare registration within political districts, compare registration and demographic data, verify your voter registration or register to vote through a link to the VoteWA, Washington State Online Voter Registration web page.

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.

Analysis of ‘US non-voters poll data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/us-non-voters-poll-datae on 28 January 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

This dataset contains the data behind Why Many Americans Don't Vote.

Data presented here comes from polling done by Ipsos for FiveThirtyEight, using Ipsos’s KnowledgePanel, a probability-based online panel that is recruited to be representative of the U.S. population. The poll was conducted from Sept. 15 to Sept. 25 among a sample of U.S. citizens that oversampled young, Black and Hispanic respondents, with 8,327 respondents, and was weighted according to general population benchmarks for U.S. citizens from the U.S. Census Bureau’s Current Population Survey March 2019 Supplement. The voter file company Aristotle then matched respondents to a voter file to more accurately understand their voting history using the panelist’s first name, last name, zip code, and eight characters of their address, using the National Change of Address program if applicable. Sixty-four percent of the sample (5,355 respondents) matched, although we also included respondents who did not match the voter file but described themselves as voting “rarely” or “never” in our survey, so as to avoid underrepresenting nonvoters, who are less likely to be included in the voter file to begin with. We dropped respondents who were only eligible to vote in three elections or fewer. We defined those who almost always vote as those who voted in all (or all but one) of the national elections (presidential and midterm) they were eligible to vote in since 2000; those who vote sometimes as those who voted in at least two elections, but fewer than all the elections they were eligible to vote in (or all but one); and those who rarely or never vote as those who voted in no elections, or just one.

The data included here is the final sample we used: 5,239 respondents who matched to the voter file and whose verified vote history we have, and 597 respondents who did not match to the voter file and described themselves as voting "rarely" or "never," all of whom have been eligible for at least 4 elections.

If you find this information useful, please let us know.

License: Creative Commons Attribution 4.0 International License

Source: https://github.com/fivethirtyeight/data/tree/master/non-voters

This dataset was created by data.world's Admin and contains around 6000 samples along with Race, Q27 6, technical information and other features such as: - Q4 6 - Q8 3 - and more.

How to use this dataset

• Analyze Q10 3 in relation to Q8 6
• Study the influence of Q6 on Q10 4
• More datasets

Acknowledgements

If you use this dataset in your research, please credit data.world's Admin

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

This county-level map shows. Voter Turnout for the 2020 U.S. Presidential election Data from County Health Rankings.Voter turnout is the percentage of citizen population aged 18 or older who voted in the 2020 U.S. Presidential election.Areas in dark blue indicate a lower voter turnout, while areas in light blue indicate a higher voter turnout. Data comes from County Health Rankings, a program of the University of Wisconsin Population Health Institute with support provided by the Robert Wood Johnson Foundation.Voting collectively influences the health of our communities and healthier communities are more likely to vote. Studies show that communities with higher voter turnout tend to also have better self-reported general health, fewer chronic health conditions, a lower overall mortality rate, and less depression. Learn more about voter turnout from County Health Rankings & Roadmaps.A number of different policies can affect voter turnout, such as voter id laws, early voting, and mail-in ballots. Learn more about voter turnout strategies and initiatives.

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 current president.

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.

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

Election Data Attribute Field Definitions | Wisconsin Cities, Towns, & Villages Data Attributes Ward Data Overview:July 2020 municipal wards were collected by LTSB through the WISE-Decade system. Current statutes require each county clerk, or board of election commissioners, no later than January 15 and July 15 of each year, to transmit to the LTSB, in an electronic format (approved by LTSB), a report confirming the boundaries of each municipality, ward and supervisory district within the county as of the preceding “snapshot” date of January 1 or July 1 respectively. Population totals for 2011 wards are carried over to the 2018 dataset for existing wards. New wards created since 2011 due to annexations, detachments, and incorporation are allocated population from Census 2010 collection blocks. LTSB has topologically integrated the data, but there may still be errors.Election Data Overview:The 1990-2000 Wisconsin election data that is included in this file was collected by LTSB from the *Wisconsin Elections Commission (WEC) after each general election. A disaggregation process was performed on this election data based on the municipal ward layer that was available at the time of the election. Disaggregation of Election Data:Election data is first disaggregated from reporting units to wards, and then to census blocks. Next, the election data is aggregated back up to wards, municipalities, and counties. The disaggregation of election data to census blocks is done based on total population. Detailed Methodology:Data is disaggregated first from reporting unit (i.e. multiple wards) to the ward level proportionate to the population of that ward. The data then is distributed down to the block level, again based on total population. When data is disaggregated to block or ward, we restrain vote totals not to exceed population 18 numbers, unless absolutely required.This methodology results in the following: Election data totals reported to the WEC at the state, county, municipal and reporting unit level should match the disaggregated election data total at the same levels. Election data totals reported to the WEC at ward level may not match the ward totals in the disaggregated election data file. Some wards may have more election data allocated than voter age population. This will occur if a change to the geography results in more voters than the 2010 historical population limits.Other things of note…We use a static, official ward layer (in this case created in 2020) to disaggregate election data to blocks. Using this ward layer creates some challenges. New wards are created every year due to annexations and incorporations. When these new wards are reported with election data, an issue arises wherein election data is being reported for wards that do not exist in our official ward layer. For example, if Cityville has four wards in the official ward layer, the election data may be reported for five wards, including a new ward from an annexation. There are two different scenarios and courses of action to these issues: When a single new ward is present in the election data but there is no ward geometry present in the official ward layer, the votes attributed to this new ward are distributed to all the other wards in the municipality based on population percentage. Distributing based on population percentage means that the proportion of the population of the municipality will receive that same proportion of votes from the new ward. In the example of Cityville explained above, the fifth ward may have five votes reported, but since there is no corresponding fifth ward in the official layer, these five votes will be assigned to each of the other wards in Cityville according the percentage of population.Another case is when a new ward is reported, but its votes are part of reporting unit. In this case, the votes for the new ward are assigned to the other wards in the reporting unit by population percentage; and not to wards in the municipality as a whole. For example, Cityville’s ward 5 was given as a reporting unit together with wards 1, 4, and 5. In this case, the votes in ward five are assigned to wards 1 and 4 according to population percentage. Outline Ward-by-Ward Election ResultsThe process of collecting election data and disaggregating to municipal wards occurs after a general election, so disaggregation has occurred with different ward layers and different population totals. We have outlined (to the best of our knowledge) what layer and population totals were used to produce these ward-by-ward election results.Election data disaggregates from WEC Reporting Unit -> Ward [Variant year outlined below]Elections 1990 – 2000: Wards 1991 (Census 1990 totals used for disaggregation)Elections 2002 – 2010: Wards 2001 (Census 2000 totals used for disaggregation)Elections 2012: Wards 2011 (Census 2010 totals used for disaggregation)Elections 2014 – 2016: Wards 2018 (Census 2010 totals used for disaggregation)Elections 2018: Wards 2018Blocks 2011 -> Centroid geometry and spatially joined with Wards [All Versions]Each Block has an assignment to each of the ward versions outlined aboveIn the event that a ward exists now in which no block exists (occurred with spring 2020) due to annexations, a block centroid was created with a population 0, and encoded with the proper Census IDs.Wards [All Versions] disaggregate -> Blocks 2011This yields a block centroid layer that contains all elections from 1990 to 2018Blocks 2011 [with all election data] -> Wards 2020 (then MCD 2020, and County 2020) All election data (including later elections) is aggregated to the Wards 2020 assignment of the blocksNotes:Population of municipal wards 1991, 2001 and 2011 used for disaggregation were determined by their respective Census.Population and Election data will be contained within a county boundary. This means that even though MCD and ward boundaries vary greatly between versions of the wards, county boundaries have stayed the same, so data should total within a county the same between wards 2011 and wards 2020.Election data may be different for the same legislative district, for the same election, due to changes in the wards from 2011 and 2020. This is due to boundary corrections in the data from 2011 to 2020, and annexations, where a block may have been reassigned.*WEC replaced the previous Government Accountability Board (GAB) in 2016, which replaced the previous State Elections Board in 2008.

This county-level map shows. Voter Turnout for the 2020 U.S. Presidential election Data from County Health Rankings.Voter turnout is the percentage of citizen population aged 18 or older who voted in the 2020 U.S. Presidential election.Areas in dark blue indicate a lower voter turnout, while areas in light blue indicate a higher voter turnout. Data comes from County Health Rankings, a program of the University of Wisconsin Population Health Institute with support provided by the Robert Wood Johnson Foundation.Voting collectively influences the health of our communities and healthier communities are more likely to vote. Studies show that communities with higher voter turnout tend to also have better self-reported general health, fewer chronic health conditions, a lower overall mortality rate, and less depression. Learn more about voter turnout from County Health Rankings & Roadmaps.A number of different policies can affect voter turnout, such as voter id laws, early voting, and mail-in ballots. Learn more about voter turnout strategies and initiatives.

According to exit polling in the 2020 Presidential Election in the United States, ** percent of surveyed voters making less than 50,000 U.S. dollars reported voting for former Vice President Joe Biden. In the race to become the next president of the United States, ** percent of voters with an income of 100,000 U.S. dollars or more reported voting for incumbent President Donald Trump.

Percentage of people who voted in the last federal, provincial and municipal elections, by groups designated as visible minorities and selected sociodemographic characteristics (age group, gender, immigrant status, generation status, first official language spoken and highest certificate, diploma or degree).

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.

For a deep dive into the data model including every specific metric, see the ACS 2016-2020 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

s

Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed

Suffixes:

_e20

Estimate from 2016-20 ACS

_m20

Margin of Error from 2016-20 ACS

_e10

2006-10 ACS, re-estimated to 2020 geography

_m10

Margin of Error from 2006-10 ACS, re-estimated to 2020 geography

_e10_20

Change, 2010-20 (holding constant at 2020 geography)

Geographies

AAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)

ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)

Census Tracts (statewide)

CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)

City (statewide)

City of Atlanta Council Districts (City of Atlanta)

City of Atlanta Neighborhood Planning Unit (City of Atlanta)

City of Atlanta Neighborhood Planning Unit STV (subarea of City of Atlanta)

City of Atlanta Neighborhood Statistical Areas (City of Atlanta)

County (statewide)

Georgia House (statewide)

Georgia Senate (statewide)

MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)

Regional Commissions (statewide)

State of Georgia (statewide)

Superdistrict (ARC region)

US Congress (statewide)

UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)

WFF = Westside Future Fund (subarea of City of Atlanta)

ZIP Code Tabulation Areas (statewide)

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2016-2020). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Source: U.S. Census Bureau, Atlanta Regional Commission Date: 2016-2020 Data License: Creative Commons Attribution 4.0 International (CC by 4.0)

Link to the manifest: https://opendata.atlantaregional.com/documents/GARC::acs-2020-data-manifest/about

As the November 2020 presidential election in the United States grows closer, voters began choosing which Democrat will run against President Donald Trump through a series of primaries. While voter turnout in presidential primaries is generally lower than turnout in presidential elections, Montana had the highest voter turnout in primaries in 2020, with **** percent of voters coming out to vote.

As of June 2025, approximately 22 percent of people in the UK would vote for the governing Labour Party in a potential general election, behind Reform UK on 28 percent, with the Conservatives third on 18 percent. Since returning to power, support for the Labour Party has fallen considerably, with the government's sinking approval rating approaching the unpopularity of the previous government. Labour's return to power in 2024 On May 22, 2024, Rishi Sunak announced his decision to hold the 2024 general election on July 4. Sunak's surprise announcement came shortly after some positive economic figures were released in the UK, and he may have hoped this would boost his poor job ratings and perhaps also his government's low approval ratings. This was a long-shot, however, and as predicted in the polls, Labour won the 2024 general election by a landslide, winning 412 out of 650 seats. The sting in the tale for the Labour Party was that despite this large majority, they won a relatively low share of the votes and almost immediately saw their popularity fall in the second half of 2024. Sunak's five pledges in 2023 After a tough 2022, in which Britain suffered through its worst cost of living crisis in a generation, the economy was consistently identified as the main issue facing the country, just ahead of healthcare. To respond to these concerns, Rishi Sunak started 2023 with five pledges; halve inflation, grow the economy, reduce national debt, cut NHS waiting times, and stop small boats. By the end of that year, just one pledge can be said to have been fully realized, with CPI inflation falling from 10.1 percent at the start of 2023 to 4 percent by the end of it. There is some ambiguity regarding the success of some of the other pledges. The economy shrank in the last two quarters of 2023 but started to grow again in early 2024. National debt increased slightly, while small boat arrivals declined compared to 2022, but were still higher than in most other years. The pledge to cut NHS waiting times was not fulfilled either, with the number of people awaiting treatment rising in 2023.