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TwitterSelected demographic, social, economic, and housing estimates data by community district/PUMA (Public Use Micro Data Sample Area). Three year estimates of population data from the Census Bureau's American Community Survey
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TwitterAs of January 2025, ** percent of social media users in the United States aged 40 to 49 years were users of Facebook, as were ** percent of ** to ** year olds in the country. Overall, ** percent of those aged 18 to 29 years were using Instagram in the U.S. The social media market in the United States The number of social media users in the United States has shown continuous growth in the past years, and it is forecast to continue increasing to reach *** million users in 2029. As of 2023, the social network user penetration in the United States amounted to an impressive ***** percent, meaning that more than nine in ten people in the country engaged with online platforms. Furthermore, Facebook was by far the most popular social media platform in the United States, accounting for ** percent of all social media visits in 2023, followed by Pinterest with **** percent of visits. The global social media landscape As of April 2024, **** billion people were social media users, accounting for **** percent of the worldβs population. Northern Europe was the region with the highest social media penetration rate with a reach of **** percent, followed by Western Europe with **** percent and Eastern Asia **** percent. In contrast, less than one in ten people in Middle Africa used social networks. Facebookβs popularity is not limited to the United States: this network leads the market on a global scale, and it accumulated more than three billion monthly active users (MAU) as of 2024, which is far more any other social media platform. YouTube, Instagram, and WhatsApp followed, all with *** billion or more MAU.
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TwitterMIT Licensehttps://opensource.org/licenses/MIT
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The dataset contains 18,944 entries with columns for Entity (country/region), Code (ISO code), Year, and Population estimates. Each row represents the population estimate for a specific country and year, spanning from 1950 to recent years, capturing global demographic changes over time.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset tabulates the Social Circle population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Social Circle. The dataset can be utilized to understand the population distribution of Social Circle by age. For example, using this dataset, we can identify the largest age group in Social Circle.
Key observations
The largest age group in Social Circle, GA was for the group of age 55-59 years with a population of 702 (14.35%), according to the 2021 American Community Survey. At the same time, the smallest age group in Social Circle, GA was the 85+ years with a population of 48 (0.98%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Social Circle Population by Age. You can refer the same here
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TwitterBy Joseph Nowicki [source]
This dataset contains demographic information about customers who have made purchases in a store, including their name, IP address, region, age, items purchased, and total amount spent. Furthermore, this data can provide insights into customer shopping behaviour for the store in question - from their geographical information to the types of products they purchase. With detailed demographic data like this at hand it is possible to make strategic decisions regarding target customers as well as developing specific marketing campaigns or promotions tailored to meet their needs and interests. By gaining deeper understanding of customer habits through this dataset we unlock more possibilities for businesses seeking higher engagement levels with shoppers
For more datasets, click here.
- π¨ Your notebook can be here! π¨!
This dataset includes information such as customer's names, IP address, age, items purchased and amount spent. This data can be used to uncover patterns in spending behavior of shoppers from different areas or regions across demographics like age group or gender.
- Analyze customer shopping trends based on age and region to maximize targetted advertising.
- Analyze the correlation between customer spending habits based on store versus online behavior.
- Use IP addresses to track geographical trends in items purchased from a particular online store to identify new markets for targeted expansion
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: Demographic_Data_Orig.csv | Column name | Description | |:---------------|:------------------------------------------------------------------------------------------------| | full.name | The full name of the customer. (String) | | ip.address | The IP address of the customer. (String) | | region | The region of residence of the customer. (String) | | in.store | A boolean value indicating whether the customer made the purchase in-store or online. (Boolean) | | age | The age of the customer. (Integer) | | items | The number of items purchased by the customer. (Integer) | | amount | The total amount spent by the customer. (Float) |
If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Joseph Nowicki.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset contains information about the demographics of all US cities and census-designated places with a population greater or equal to 65,000.
This data comes from the US Census Bureau's 2015 American Community Survey.
This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau.
Foto von Andrew Neel auf Unsplash
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TwitterThe American Community Survey (ACS) is an ongoing annual survey on a range of social, economic, demographic, and housing characteristics of the US population. For the purpose of our research study, we used the 5-year tabulations, which gave access to zipcode- and tract-level estimates of the variables.
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Twitterhttps://www.icpsr.umich.edu/web/ICPSR/studies/7529/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/7529/terms
Prepared by ICPSR under a project to automate major portions of the Statistique Generale de la France, this is a collection of demographic, social, education, economic, population, and vital statistics data for France, 1833-1925. This conversion project is a continuation of one conducted in 1972, for which a similar data collection was created, SOCIAL, DEMOGRAPHIC, AND EDUCATIONAL DATA FOR FRANCE, 1801-1897 (ICPSR 0048). The project to collect and prepare these data was sponsored by two French and two American groups: ICPSR and the Center for Western European Studies at the University of Michigan, and the Fourth and Sixth Sections of the Ecole Pratique des Hautes Etudes and Conseil National de la Recherches Scientifique in France. Both collections include data recorded at the departement, arrondissement, chef-lieu, and ville level. In this collection, materials from the vital statistics series were prepared for selected years rather than for each year in the period from 1900-1925. The years that were chosen clustered around the quinquennial censuses and also included (because of the violent demographic dislocations produced by World War I) each year in the 1914-1919 period. In addition, some vital statistics for the nineteenth century (1836-1850, 1880, and 1892) obtained from fugitive published volumes that could not be located during the course of the 1972 project were prepared. The 136 datasets in this collection contain: (1) French population, economic, and social data obtained from the quenquennial censuses of 1901, 1906, 1911, and 1921, that detail the composition of the population by categories of age, sex, nativity, marital status, religion, place of residence, and occupation, (2) industrial census data for the years 1861-1896, (3) data on primary education in France for 1833, 1901, and 1906, as well as data on secondary and higher education in France for the years 1836-1850, 1880, and 1892, and (4) data from a separate series of annual vital statistics (Mouvement de la Population) that cover the years 1836-1850, 1892, and 1900-1925, citing births, deaths, and marriages in the nation.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the data for the Social Circle, GA population pyramid, which represents the Social Circle population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey 5-Year estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Social Circle Population by Age. You can refer the same here
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TwitterCC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Survey data collected in Canada, 2019. n = 1539. Using, Age, Facebook use and meme understanding to determine differences between demographics in relation to Instagram use
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TwitterBy Danny [source]
This dataset contains US county-level demographic data from 2016, giving insight into the health and economic conditions of counties in the United States. Aggregated and filtered from various sources such as the US Census Small Area Income and Poverty Estimates (SAIPE) Program, American Community Survey, CDC National Center for Health Statistics, and more, this comprehensive dataset provides information on population as well as desert population for each county. Additionally, data is split between metropolitan and nonmetropolitan areas according to the Office of Management and Budget's 2013 classification scheme. Valuable information pertaining to infant mortality rates and total population are also included in this detailed set of data. Use this dataset to gain a better understanding of one of our nation's most essential regions
For more datasets, click here.
- π¨ Your notebook can be here! π¨!
- Look at the information within the 'About this Dataset' section to have an understanding of what data sources were used to create this dataset as well as any transformations that may have been done while creating it.
- Familiarize yourself with the columns provided in the data set to understand what information is available for each county such as total population (totpop), parental education level (educationLvl), median household income (medianIncome), etc.,
- Use a combination of filtering and sorting techniques to narrow down results and focus in on more specific county demographics that you are looking for such as total households living below poverty line by state or median household income per capita between two counties etc.,
- Keep in mind any additional transformations/simplifications/aggregations done during step 2 when using your data for analysis. For example, if certain variables were pivoted during step two from being rows into columns because it was easier to work with multiple years of income levels by having them all consolidated into one column then be aware that some states may not appear in all records due to those transformations being applied differently between regions which could result in missing values or other inconsistencies when doing downstream analysis on your selected variables.
- Utilize resources such as Wikipedia and government census estimates if you need more detailed information surrounding these demographic characteristics beyond what's available within our current dataset β these can be helpful when conducting further research outside of solely relying on our provided spreadsheet values alone!
- Creating a US county-level heat map of infant mortality rates, offering insight into which areas are most at risk for poor health outcomes.
- Generating predictive models from the population data to anticipate and prepare for future population trends in different states or regions.
- Developing an interactive web-based tool for school districts to explore potential impacts of student mobility on their area's population stability and diversity
If you use this dataset in your research, please credit the original authors. Data Source
License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.
File: Food Desert.csv | Column name | Description | |:--------------------|:----------------------------------------------------------------------------------| | year | The year the data was collected. (Integer) | | fips | The Federal Information Processing Standard (FIPS) code for the county. (Integer) | | state_fips | The FIPS code for the state. (Integer) | | county_fips | The FIPS code for the county. (Integer)...
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TwitterThis data collection contains detailed county and state-level ecological and descriptive data for the United States for the years 1790 to 2002. Parts 1-43 are an update to HISTORICAL, DEMOGRAPHIC, ECONOMIC, AND SOCIAL DATA: THE UNITED STATES, 1790-1970 (ICPSR 0003). Parts 1-41 contain data from the 1790-1970 censuses. They include extensive information about the social and political character of the United States, including a breakdown of population by state, race, nationality, number of families, size of the family, births, deaths, marriages, occupation, religion, and general economic condition. Parts 42 and 43 contain data from the 1840 and 1870 Censuses of Manufacturing, respectively. These files include information about the number of persons employed in various industries and the quantities of different types of manufactured products. Parts 44-50 provide county-level data from the United States Census of Agriculture for 1840 to 1900. They also include the state and national totals for the variables. The files provide data about the number, types, and prices of various agricultural products. Parts 51-57 contain data on religious bodies and church membership for 1906, 1916, 1926, 1936, and 1952, respectively. Parts 58-69 consist of data from the CITY DATA BOOKS for 1944, 1948, 1952, 1956, 1962, 1967, 1972, 1977, 1983, 1988, 1994, and 2000, respectively. These files contain information about population, climate, housing units, hotels, birth and death rates, school enrollment and education expenditures, employment in various industries, and city government finances. Parts 70-81 consist of data from the COUNTY DATA BOOKS for 1947, 1949, 1952, 1956, 1962, 1967, 1972, 1977, 1983, 1988, 1994, and 2000, respectively. These files include information about population, employment, housing, agriculture, manufacturing, retail, services, trade, banking, Social Security, local governments, school enrollment, hospitals, crime, and income. Parts 82-84 contain data from USA COUNTIES 1998. Due to the large number of variables from this source, the data were divided into into three separate data files. Data include information on population, vital statistics, school enrollment, educational attainment, Social Security, labor force, personal income, poverty, housing, trade, farms, ancestry, commercial banks, and transfer payments. Parts 85-106 provide data from the United States Census of Agriculture for 1910 to 2002. They provide data about the amount, types, and prices of various agricultural products. Also, these datasets contain extensive information on the amount, expenses, sales, values, and production of farms and machinery. (Source: downloaded from ICPSR 7/13/10)
Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR02896.v3. We highly recommend using the ICPSR version, as they made this dataset available in multiple data formats and updated the data through 2002.
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TwitterAccording to a survey of social media users aged between 16 and 34 years old in the United States, as of **********, the majority of respondents reported following social media influencers in which they saw similar demographic characteristics as they had, such as age, gender, or lifestyle. By comparison, approximately ** percent of respondents reported not following influencers within similar demographics.
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TwitterThe Annual Social and Economic Supplement or March CPS supplement is the primary source of detailed information on income and work experience in the United States. Numerous publications based on this survey are issued each year by the Bureaus of Labor Statistics and Census. A public-use microdata file is available for private researchers, who also produce many academic and policy-related documents based on these data. The Annual Social and Economic Supplement is used to generate the annual Population Profile of the United States, reports on geographical mobility and educational attainment, and detailed analysis of money income and poverty status. The labor force and work experience data from this survey are used to profile the U.S. labor market and to make employment projections. To allow for the same type of in-depth analysis of hispanics, additional hispanic sample units are added to the basic CPS sample in March each year. Additional weighting is also performed so that estimates can be made for households and families, in addition to persons.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset was created by MarkSchultz
Released under CC0: Public Domain
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TwitterApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset was created by Niharika Tiwari
Released under Apache 2.0
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TwitterU.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
This census tract geography dataset includes selected indicators (2012-2016 5-Year Averages) pertaining to population, age, race/ethnicity, language, housing, poverty/income, education, disability, health insurance, employment, and age*race*gender groups. This dataset is assembled annually from the U.S. Census American Community Survey American Factfinder website and is maintained by the Colorado Department of Public Health and Environment.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Data associated with the paper: Who Tweets with Their Location? Understanding the Relationship Between Demographic Characteristics and the Use of Geoservices and Geotagging on Twitter Luke Sloan & Jeffrey Morgan
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Wellbeing statistics: 2021 (supplementary) presents supplementary data from the 2021 General Social Survey (GSS), adding to the data released in Wellbeing statistics: 2021 in July 2022.
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TwitterSocial demographic characteristics of participants.
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TwitterSelected demographic, social, economic, and housing estimates data by community district/PUMA (Public Use Micro Data Sample Area). Three year estimates of population data from the Census Bureau's American Community Survey