The Survey of Consumer Finances (SCF) is normally a triennial cross-sectional survey of U.S. families. The survey data include information on families' balance sheets, pensions, income, and demographic characteristics.

US Broadband Usage Across Counties

Utilizing Microsoft's Data to Estimate Access

By Amber Thomas [source]

About this dataset

This dataset provides an estimation of broadband usage in the United States, focusing on how many people have access to broadband and how many are actually using it at broadband speeds. Through data collected by Microsoft from our services, including package size and total time of download, we can estimate the throughput speed of devices connecting to the internet across zip codes and counties.

According to Federal Communications Commission (FCC) estimates, 14.5 million people don't have access to any kind of broadband connection. This data set aims to address this contrast between those with estimated availability but no actual use by providing more accurate usage numbers downscaled to county and zip code levels. Who gets counted as having access is vastly important -- it determines who gets included in public funding opportunities dedicated solely toward closing this digital divide gap. The implications can be huge: millions around this country could remain invisible if these number aren't accurately reported or used properly in decision-making processes.

This dataset includes aggregated information about these locations with less than 20 devices for increased accuracy when estimating Broadband Usage in the United States-- allowing others to use it for developing solutions that improve internet access or label problem areas accurately where no real or reliable connectivity exists among citizens within communities large and small throughout the US mainland.. Please review the license terms before using these data so that you may adhere appropriately with stipulations set forth under Microsoft's Open Use Of Data Agreement v1.0 agreement prior to utilizing this dataset for your needs-- both professional and educational endeavors alike!

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How to use the dataset

How to Use the US Broadband Usage Dataset

This dataset provides broadband usage estimates in the United States by county and zip code. It is ideally suited for research into how broadband connects households, towns and cities. Understanding this information is vital for closing existing disparities in access to high-speed internet, and for devising strategies for making sure all Americans can stay connected in a digital world.

The dataset contains six columns: - County – The name of the county for which usage statistics are provided. - Zip Code (5-Digit) – The 5-digit zip code from which usage data was collected from within that county or metropolitan area/micro area/divisions within states as reported by the US Census Bureau in 2018[2].
- Population (Households) – Estimated number of households defined according to [3] based on data from the US Census Bureau American Community Survey's 5 Year Estimates[4].
- Average Throughput (Mbps)- Average Mbps download speed derived from a combination of data collected anonymous devices connected through Microsoft services such as Windows Update, Office 365, Xbox Live Core Services, etc.[5]
- Percent Fast (> 25 Mbps)- Percentage of machines with throughput greater than 25 Mbps calculated using [6]. 6) Percent Slow (< 3 Mbps)- Percentage of machines with throughput less than 3Mbps calculated using [7].

Research Ideas

• Targeting marketing campaigns based on broadband use. Companies can use the geographic and demographic data in this dataset to create targeted advertising campaigns that are tailored to individuals living in areas where broadband access is scarce or lacking.
• Creating an educational platform for those without reliable access to broadband internet. By leveraging existing technologies such as satellite internet, media streaming services like Netflix, and platforms such as Khan Academy or EdX, those with limited access could gain access to new educational options from home.
• Establishing public-private partnerships between local governments and telecom providers need better data about gaps in service coverage and usage levels in order to make decisions about investments into new infrastructure buildouts for better connectivity options for rural communities

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: broadband_data_2020October.csv

Acknowledgements

If you use this dataset in your research,...

About this dataset

Context

The dataset tabulates the New York County population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of New York County. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 1.11 million (68.12% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the New York County population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in New York County is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the New York County is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for New York County Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Miami-Dade County population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Miami-Dade County. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 1.69 million (63.03% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Miami-Dade County population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Miami-Dade County is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Miami-Dade County is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Miami-Dade County Population by Age. You can refer the same here

Which county has the most Facebook users?

              There are more than 378 million Facebook users in India alone, making it the leading country in terms of Facebook audience size. To put this into context, if India’s Facebook audience were a country then it would be ranked third in terms of largest population worldwide. Apart from India, there are several other markets with more than 100 million Facebook users each: The United States, Indonesia, and Brazil with 193.8 million, 119.05 million, and 112.55 million Facebook users respectively.

              Facebook – the most used social media

              Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3,5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising.

              Facebook usage by device
              As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.

Cristiano Ronaldo has one of the most popular Instagram accounts as of April 2024.

              The Portuguese footballer is the most-followed person on the photo sharing app platform with 628 million followers. Instagram's own account was ranked first with roughly 672 million followers.

              How popular is Instagram?

              Instagram is a photo-sharing social networking service that enables users to take pictures and edit them with filters. The platform allows users to post and share their images online and directly with their friends and followers on the social network. The cross-platform app reached one billion monthly active users in mid-2018. In 2020, there were over 114 million Instagram users in the United States and experts project this figure to surpass 127 million users in 2023.

              Who uses Instagram?

              Instagram audiences are predominantly young – recent data states that almost 60 percent of U.S. Instagram users are aged 34 years or younger. Fall 2020 data reveals that Instagram is also one of the most popular social media for teens and one of the social networks with the biggest reach among teens in the United States.

              Celebrity influencers on Instagram
              Many celebrities and athletes are brand spokespeople and generate additional income with social media advertising and sponsored content. Unsurprisingly, Ronaldo ranked first again, as the average media value of one of his Instagram posts was 985,441 U.S. dollars.

About this dataset

Context

The dataset tabulates the Missouri population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Missouri. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 3.7 million (60.03% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Missouri population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Missouri is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Missouri is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Missouri Population by Age. You can refer the same here

Money Supply M2 in the United States increased to 21942 USD Billion in May from 21862.40 USD Billion in April of 2025. This dataset provides - United States Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The index ranges from 0.0, when all families (households) have equal shares of income (implies perfect equality), to 1.0 when one family (household) has all the income and the rest have none (implies perfect inequality). Index data is provided for California and its counties, regions, and large cities/towns. The data is from the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Income is linked to acquiring resources for healthy living. Both household income and the distribution of income across a society independently contribute to the overall health status of a community. On average Western industrialized nations with large disparities in income distribution tend to have poorer health status than similarly advanced nations with a more equitable distribution of income. Approximately 119,200 (5%) of the 2.4 million U.S. deaths in 2000 are attributable to income inequality. The pathways by which income inequality act to increase adverse health outcomes are not known with certainty, but policies that provide for a strong safety net of health and social services have been identified as potential buffers.Dataset taken from https://data.chhs.ca.gov/dataset/income-inequalityData Dictionary: COLUMN NAMEDEFINITIONFORMATCODINGind_idIndicator IDPlain Text770ind_definitionDefinition of indicator in plain languagePlain TextFree textreportyearYear(s) that the indicator was reportedPlain Text2005-2007, 2008-2010, 2006-2010. 2005-2007, 2008-2010, and 2006-2010 data is from the American Community Survey (ACS), U.S. Census Bureau. The ACS is a continuous survey. ACS estimates are period estimates that describe the average characteristics of the population in a period of data collection. The multiyear estimates are averages of the characteristics over several years. For example, the 2005-2007 ACS 3-year estimates are averages over the period from January 1, 2005 to December 31, 2007. Multiyear estimates cannot be used to say what was going on in any particular year in the period, only what the average value is over the full time period (Source: http://www.census.gov/acs/www/about_the_survey/american_community_survey/).race_eth_codenumeric code for a race/ethnicity groupPlain Text9=Totalrace_eth_nameName of race/ethnic groupPlain Text9=TotalgeotypeType of geographic unitPlain TextPL=Place (includes cities, towns, and census designated places -CDP-. It does not include unincorporated communities); CO=County; RE=region; CA=StategeotypevalueValue of geographic unitPlain Text9-digit Census tract code; 5-digit FIPS place code; 5-digit FIPS county code; 2-digit region ID; 2-digit FIPS state codegeonameName of geographic unitPlain Textplace name, county name, region name, or state namecounty_nameName of county that geotype is inPlain TextNot available for geotypes RE and CAcounty_fipsFIPS code of county that geotype is inPlain Text2-digit census state code (06) plus 3-digit census county coderegion_nameMetopolitan Planning Organization (MPO)-based region name: see MPO_County List TabPlain TextMetropolitan Planning Organizations (MPO) regions as reported in the 2010 California Regional Progress Report (http://www.dot.ca.gov/hq/tpp/offices/orip/Collaborative%20Planning/Files/CARegionalProgress_2-1-2011.pdf).region_codeMetopolitan Planning Organization (MPO)-based region code: see MPO_CountyList tabPlain Text01=Bay Area; 08=Sacramento Area; 09=San Diego; 14=Southern CaliforniaNumber_HouseholdsNumber of households in a jurisdictionNumericGini_indexCumulative percentage of household income relative to the cumulative percentage of the number of households expressed on a 0 to 1 scale called the Gini Index. The index ranges from 0.0, when all families (households) have equal shares of income, to 1.0, when one family (household) has all the income and the rest none (https://www.census.gov/prod/2000pubs/p60-204.pdf).NumericLL_95CILower limit of 95% confidence intervalNumericLower limit of 95% confidence interval. The 95% confidence limits depict the range within which the percentage would probably occur in 95 of 100 sets of data (if data similar to the present set were independently acquired on 100 separate occasions). In five of those 100 data sets, the percentage would fall outside the limits.UL_95CIUpper limit of 95% confidence intervalNumericUpper limit of 95% confidence interval. The 95% confidence limits depict the range within which the percentage would probably occur in 95 of 100 sets of data (if data similar to the present set were independently acquired on 100 separate occasions). In five of those 100 data sets, the percentage would fall outside the limits.seStandard error of percent NumericThe standard error (SE) of the estimate of the mean is a measure of the precision of the sample mean. The standard error falls as the sample size increases. (Reference: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1255808/)rseRelative standard error (se/percent * 100) expressed as a percentNumericThe relative standard error (RSE) provides the rational basis for determining which rates may be considered “unreliable.” Conforming to National Center for Health Statistics (NCHS) standards, rates that are calculated from fewer than 20 data elements, the equivalent of an RSE of 23 percent or more, are considered unreliable. From: http://www.cdph.ca.gov/programs/ohir/Documents/OHIRProfiles2014.pdfCA_decileDecilesNumeric"CA_decile" groups places or census tracts into 10 groups (or deciles) according to the distribution of values of the index (Gini_index). The first decile (1) corresponds to the highest Gini indices; the tenth decile (10) corresponds to the lowest Gini indices. Equal values or 'ties' are assigned the mean decile rank. For example, in a database of 100 records where 70 records equal 0, 0 values span from the 1st to 7th deciles (70% of all data records). As a result, all 0 values will be assigned to the 4th decile: the mean between the 1st and 7th deciles. The deciles are only calculated for places and/or census tracts.CA_RRIndex ratio to state indexNumericRatio of local index to state index. This indicates how many times the local index is higher or lower than the state index (Reference: http://health.mo.gov/training/epi/RateRatio-b.html). Values higher than 1 indicate local index is higher than state index.Median_HH_incomeMedian household income data is provided for users to stratify the Gini index by income deciles for places and countiesNumericMedian_HH_decileMedian household income data is provided for users to stratify the Gini index by income deciles for places and countiesNumericversionDate/time stamp of version of dataDate/Timemm/DD/CCYY hh:mm:ss

About this dataset

Context

The dataset tabulates the San Diego County population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of San Diego County. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 2.09 million (63.81% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the San Diego County population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in San Diego County is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the San Diego County is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for San Diego County Population by Age. You can refer the same here

Time series data for the statistic Adjusted savings: particulate emission damage (current US$) and country Georgia. Indicator Definition:Particulate emissions damage is the damage due to exposure of a country's population to ambient concentrations of particulates measuring less than 2.5 microns in diameter (PM2.5), ambient ozone pollution, and indoor concentrations of PM2.5 in households cooking with solid fuels. Damages are calculated as foregone labor income due to premature death. Estimates of health impacts from the Global Burden of Disease Study 2013 are for 1990, 1995, 2000, 2005, 2010, and 2013. Data for other years have been extrapolated from trends in mortality rates.The indicator "Adjusted savings: particulate emission damage (current US$)" stands at 87.93 Million usd as of 12/31/2021, the highest value since 12/31/1991. Regarding the One-Year-Change of the series, the current value constitutes an increase of 9.52 percent compared to the value the year prior.The 1 year change in percent is 9.52.The 3 year change in percent is 9.52.The 5 year change in percent is 14.01.The 10 year change in percent is 19.05.The Serie's long term average value is 60.41 Million usd. It's latest available value, on 12/31/2021, is 45.56 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/1999, to it's latest available value, on 12/31/2021, is +173.11%.The Serie's change in percent from it's maximum value, on 12/31/1990, to it's latest available value, on 12/31/2021, is -4.69%.

The number of social media users in the United States was forecast to continuously increase between 2024 and 2029 by in total 26 million users (+8.55 percent). After the ninth consecutive increasing year, the social media user base is estimated to reach 330.07 million users and therefore a new peak in 2029. Notably, the number of social media users of was continuously increasing over the past years.The shown figures regarding social media users have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

Time series data for the statistic Adjusted savings: particulate emission damage (current US$) and country Uruguay. Indicator Definition:Particulate emissions damage is the damage due to exposure of a country's population to ambient concentrations of particulates measuring less than 2.5 microns in diameter (PM2.5), ambient ozone pollution, and indoor concentrations of PM2.5 in households cooking with solid fuels. Damages are calculated as foregone labor income due to premature death. Estimates of health impacts from the Global Burden of Disease Study 2013 are for 1990, 1995, 2000, 2005, 2010, and 2013. Data for other years have been extrapolated from trends in mortality rates.The indicator "Adjusted savings: particulate emission damage (current US$)" stands at 38.32 Million usd as of 12/31/2021. Regarding the One-Year-Change of the series, the current value constitutes an increase of 6.33 percent compared to the value the year prior.The 1 year change in percent is 6.33.The 3 year change in percent is -4.93.The 5 year change in percent is 2.61.The 10 year change in percent is 9.28.The Serie's long term average value is 28.99 Million usd. It's latest available value, on 12/31/2021, is 32.16 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2004, to it's latest available value, on 12/31/2021, is +166.15%.The Serie's change in percent from it's maximum value, on 12/31/2018, to it's latest available value, on 12/31/2021, is -4.93%.

This dataset displays the energy prices and expenditures for each of the 50 United States, plus the District of Columbia. Included in the dataset are figures on the prices on a scale with nominal dollars per million Btu. Expenditures in millions of nominal dollars. Expenditures per person in nominal dollars. Hawaii pays the highest in prices, with Texas paying the most in expenditures.

About this dataset

Context

The dataset tabulates the Ohio population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Ohio. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 7.07 million (59.99% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Ohio population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Ohio is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Ohio is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Ohio Population by Age. You can refer the same here

In the fourth quarter of 2024, TikTok generated around 186 million downloads from users worldwide. Initially launched in China first by ByteDance as Douyin, the short-video format was popularized by TikTok and took over the global social media environment in 2020. In the first quarter of 2020, TikTok downloads peaked at over 313.5 million worldwide, up by 62.3 percent compared to the first quarter of 2019.

              TikTok interactions: is there a magic formula for content success?

              In 2024, TikTok registered an engagement rate of approximately 4.64 percent on video content hosted on its platform. During the same examined year, the social video app recorded over 1,100 interactions on average. These interactions were primarily composed of likes, while only recording less than 20 comments per piece of content on average in 2024.
              The platform has been actively monitoring the issue of fake interactions, as it removed around 236 million fake likes during the first quarter of 2024. Though there is no secret formula to get the maximum of these metrics, recommended video length can possibly contribute to the success of content on TikTok.
              It was recommended that tiny TikTok accounts with up to 500 followers post videos that are around 2.6 minutes long as of the first quarter of 2024. While, the ideal video duration for huge TikTok accounts with over 50,000 followers was 7.28 minutes. The average length of TikTok videos posted by the creators in 2024 was around 43 seconds.

              What’s trending on TikTok Shop?

              Since its launch in September 2023, TikTok Shop has become one of the most popular online shopping platforms, offering consumers a wide variety of products. In 2023, TikTok shops featuring beauty and personal care items sold over 370 million products worldwide.
              TikTok shops featuring womenswear and underwear, as well as food and beverages, followed with 285 and 138 million products sold, respectively. Similarly, in the United States market, health and beauty products were the most-selling items,
              accounting for 85 percent of sales made via the TikTok Shop feature during the first month of its launch. In 2023, Indonesia was the market with the largest number of TikTok Shops, hosting over 20 percent of all TikTok Shops. Thailand and Vietnam followed with 18.29 and 17.54 percent of the total shops listed on the famous short video platform, respectively.

Time series data for the statistic Adjusted savings: particulate emission damage (current US$) and country Djibouti. Indicator Definition:Particulate emissions damage is the damage due to exposure of a country's population to ambient concentrations of particulates measuring less than 2.5 microns in diameter (PM2.5), ambient ozone pollution, and indoor concentrations of PM2.5 in households cooking with solid fuels. Damages are calculated as foregone labor income due to premature death. Estimates of health impacts from the Global Burden of Disease Study 2013 are for 1990, 1995, 2000, 2005, 2010, and 2013. Data for other years have been extrapolated from trends in mortality rates.The indicator "Adjusted savings: particulate emission damage (current US$)" stands at 67.02 Million usd as of 12/31/2021, the highest value at least since 12/31/1991, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes an increase of 5.47 percent compared to the value the year prior.The 1 year change in percent is 5.47.The 3 year change in percent is 11.11.The 5 year change in percent is 21.81.The 10 year change in percent is 108.17.The Serie's long term average value is 32.70 Million usd. It's latest available value, on 12/31/2021, is 104.97 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/1991, to it's latest available value, on 12/31/2021, is +241.08%.The Serie's change in percent from it's maximum value, on 12/31/2021, to it's latest available value, on 12/31/2021, is 0.0%.

Time series data for the statistic Adjusted savings: particulate emission damage (current US$) and country Belarus. Indicator Definition:Particulate emissions damage is the damage due to exposure of a country's population to ambient concentrations of particulates measuring less than 2.5 microns in diameter (PM2.5), ambient ozone pollution, and indoor concentrations of PM2.5 in households cooking with solid fuels. Damages are calculated as foregone labor income due to premature death. Estimates of health impacts from the Global Burden of Disease Study 2013 are for 1990, 1995, 2000, 2005, 2010, and 2013. Data for other years have been extrapolated from trends in mortality rates.The indicator "Adjusted savings: particulate emission damage (current US$)" stands at 120.77 Million usd as of 12/31/2021, the highest value since 12/31/2015. Regarding the One-Year-Change of the series, the current value constitutes an increase of 10.41 percent compared to the value the year prior.The 1 year change in percent is 10.41.The 3 year change in percent is 11.73.The 5 year change in percent is 31.83.The 10 year change in percent is -28.47.The Serie's long term average value is 91.96 Million usd. It's latest available value, on 12/31/2021, is 31.33 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2000, to it's latest available value, on 12/31/2021, is +221.92%.The Serie's change in percent from it's maximum value, on 12/31/2011, to it's latest available value, on 12/31/2021, is -28.47%.

Instagram’s most popular post

              As of April 2024, the most popular post on Instagram was Lionel Messi and his teammates after winning the 2022 FIFA World Cup with Argentina, posted by the account @leomessi. Messi's post, which racked up over 61 million likes within a day, knocked off the reigning post, which was 'Photo of an Egg'. Originally posted in January 2021, 'Photo of an Egg' surpassed the world’s most popular Instagram post at that time, which was a photo by Kylie Jenner’s daughter totaling 18 million likes.
              After several cryptic posts published by the account, World Record Egg revealed itself to be a part of a mental health campaign aimed at the pressures of social media use.

              Instagram’s most popular accounts

              As of April 2024, the official Instagram account @instagram had the most followers of any account on the platform, with 672 million followers. Portuguese footballer Cristiano Ronaldo (@cristiano) was the most followed individual with 628 million followers, while Selena Gomez (@selenagomez) was the most followed woman on the platform with 429 million. Additionally, Inter Miami CF striker Lionel Messi (@leomessi) had a total of 502 million. Celebrities such as The Rock, Kylie Jenner, and Ariana Grande all had over 380 million followers each.

              Instagram influencers

              In the United States, the leading content category of Instagram influencers was lifestyle, with 15.25 percent of influencers creating lifestyle content in 2021. Music ranked in second place with 10.96 percent, followed by family with 8.24 percent. Having a large audience can be very lucrative: Instagram influencers in the United States, Canada and the United Kingdom with over 90,000 followers made around 1,221 US dollars per post.

              Instagram around the globe

              Instagram’s worldwide popularity continues to grow, and India is the leading country in terms of number of users, with over 362.9 million users as of January 2024. The United States had 169.65 million Instagram users and Brazil had 134.6 million users. The social media platform was also very popular in Indonesia and Turkey, with 100.9 and 57.1, respectively. As of January 2024, Instagram was the fourth most popular social network in the world, behind Facebook, YouTube and WhatsApp.

About this dataset

Context

The dataset tabulates the Oregon population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Oregon. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 2.59 million (61.17% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Oregon population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Oregon is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Oregon is shown in the following column.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Oregon Population by Age. You can refer the same here