About this dataset

Context

The dataset tabulates the United States population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of United States across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2024, the population of United States was 340.11 million, a 0.98% increase year-by-year from 2023. Previously, in 2023, United States population was 336.81 million, an increase of 0.83% compared to a population of 334.02 million in 2022. Over the last 20 plus years, between 2000 and 2024, population of United States increased by 57.95 million. In this period, the peak population was 340.11 million in the year 2024. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2024

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2024)
• Population: The population for the specific year for the United States is shown in this column.
• Year on Year Change: This column displays the change in United States population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 United States Population by Year. You can refer the same here

The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on earth, which far exceeds the world population of 7.2 billion from 2015. Our own estimate based on UN data shows the world's population surpassing 7.7 billion.

China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, the country of India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.

The next 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.

Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.

In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added each year.

This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by the year 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

Global life expectancy has also improved in recent years, increasing the overall population life expectancy at birth to just over 70 years of age. The projected global life expectancy is only expected to continue to improve - reaching nearly 77 years of age by the year 2050. Significant factors impacting the data on life expectancy include the projections of the ability to reduce AIDS/HIV impact, as well as reducing the rates of infectious and non-communicable diseases.

Population aging has a massive impact on the ability of the population to maintain what is called a support ratio. One key finding from 2017 is that the majority of the world is going to face considerable growth in the 60 plus age bracket. This will put enormous strain on the younger age groups as the elderly population is becoming so vast without the number of births to maintain a healthy support ratio.

Although the number given above seems very precise, it is important to remember that it is just an estimate. It simply isn't possible to be sure exactly how many people there are on the earth at any one time, and there are conflicting estimates of the global population in 2016.

Some, including the UN, believe that a population of 7 billion was reached in October 2011. Others, including the US Census Bureau and World Bank, believe that the total population of the world reached 7 billion in 2012, around March or April.

The world population surpassed eight billion people in 2022, having doubled from its figure less than 50 years previously. Looking forward, it is projected that the world population will reach nine billion in 2038, and 10 billion in 2060, but it will peak around 10.3 billion in the 2080s before it then goes into decline. Regional variations The global population has seen rapid growth since the early 1800s, due to advances in areas such as food production, healthcare, water safety, education, and infrastructure, however, these changes did not occur at a uniform time or pace across the world. Broadly speaking, the first regions to undergo their demographic transitions were Europe, North America, and Oceania, followed by Latin America and Asia (although Asia's development saw the greatest variation due to its size), while Africa was the last continent to undergo this transformation. Because of these differences, many so-called "advanced" countries are now experiencing population decline, particularly in Europe and East Asia, while the fastest population growth rates are found in Sub-Saharan Africa. In fact, the roughly two billion difference in population between now and the 2080s' peak will be found in Sub-Saharan Africa, which will rise from 1.2 billion to 3.2 billion in this time (although populations in other continents will also fluctuate). Changing projections The United Nations releases their World Population Prospects report every 1-2 years, and this is widely considered the foremost demographic dataset in the world. However, recent years have seen a notable decline in projections when the global population will peak, and at what number. Previous reports in the 2010s had suggested a peak of over 11 billion people, and that population growth would continue into the 2100s, however a sooner and shorter peak is now projected. Reasons for this include a more rapid population decline in East Asia and Europe, particularly China, as well as a prolonged development arc in Sub-Saharan Africa.

this graph was created in PowerBi,Loocker and Tableau:

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We can’t understand the world without understanding demographic change.

How many people are alive today? How many are born; how many die? What do we expect populations to look like in the future?

The United Nations updates its big dataset — the World Population Prospects — every two years to answer these questions. It just released its latest edition today.

We’ve updated all of our population-related datasets and charts with this new release. You can explore all the trends for every country in our Population and Demography Data Explorer.

In this article, we wanted to provide key insights from this latest wave of data.

The world population is projected to peak slightly earlier than in previous projections The United Nations doesn’t only publish historical estimates of how population and demographic trends have changed in the past; it also makes projections for what the future might look like. To be clear, these are projections, not predictions of changes in the future.

In its 2022 publication, the UN estimated that, in its medium scenario, the global population would peak in 2086 at around 10.4 billion people.

This year’s edition brings this peak forward slightly to 2084, with the population topping at just under 10.3 billion.

The chart below compares the two revisions.

This isn’t the first time the projected peak has been pulled earlier. According to its 2019 edition, the global population would reach 10.9 billion by 2100 and keep growing. The 2022 revision was the first to project a peak in the 21st century. Not every country has seen a drop in projected population compared to the last edition. The chart below shows the differences between the two UN revisions, region by region. Note that the vertical axis scale for each region is different, allowing you to see the changes more clearly.

The latest UN revision has downgraded its future population estimates in Asia, Africa, and Latin America but increased its projections for Europe and North America.

Context

In demographics, the world population is the total number of humans currently living, and was estimated to have reached 7,800,000,000 people as of March 2020. It took over 2 million years of human history for the world's population to reach 1 billion, and only 200 years more to reach 7 billion. The world population has experienced continuous growth following the Great Famine of 1315–1317 and the end of the Black Death in 1350, when it was near 370 million. The highest global population growth rates, with increases of over 1.8% per year, occurred between 1955 and 1975 – peaking to 2.1% between 1965 and 1970.[7] The growth rate declined to 1.2% between 2010 and 2015 and is projected to decline further in the course of the 21st century. However, the global population is still increasing[8] and is projected to reach about 10 billion in 2050 and more than 11 billion in 2100.

Content

Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. Annual population growth rate. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Statistical Concept and Methodology

Total population growth rates are calculated on the assumption that rate of growth is constant between two points in time. The growth rate is computed using the exponential growth formula: r = ln(pn/p0)/n, where r is the exponential rate of growth, ln() is the natural logarithm, pn is the end period population, p0 is the beginning period population, and n is the number of years in between. Note that this is not the geometric growth rate used to compute compound growth over discrete periods. For information on total population from which the growth rates are calculated, see total population (SP.POP.TOTL).

Acknowledgements

Derived from total population. Population source: ( 1 ) United Nations Population Division. World Population Prospects: 2019 Revision, ( 2 ) Census reports and other statistical publications from national statistical offices, ( 3 ) Eurostat: Demographic Statistics, ( 4 ) United Nations Statistical Division. Population and Vital Statistics Reprot ( various years ), ( 5 ) U.S. Census Bureau: International Database, and ( 6 ) Secretariat of the Pacific Community: Statistics and Demography Programme.

The analysis of the world's population is a complex and multifaceted endeavor, encompassing a wide range of demographic, economic, social, and environmental factors. Understanding these trends and dynamics is crucial for policymakers, researchers, and organizations to make informed decisions and plan for the future. This article delves into a comprehensive analysis of the world's population, examining its growth patterns, demographic shifts, challenges, and opportunities.

Population Growth. The world's population has experienced remarkable growth over the past century. In 1927, the global population reached its first billion, and since then, it has surged exponentially. As of the latest available data in 2021, the world's population stands at approximately 7.8 billion. Projections indicate that this figure will continue to rise, with estimates suggesting a population of over 9 billion by 2050.

Factors Driving Population Growth. 1. Fertility Rates: High birth rates, particularly in developing countries, have been a significant driver of population growth. Access to healthcare, education, and family planning services plays a crucial role in reducing fertility rates. 2. Increased Life Expectancy: Improvements in healthcare, nutrition, and sanitation have led to longer life expectancy worldwide. This has contributed to population growth, as people are living longer and healthier lives. 3. Demographic Shifts: Demographic shifts are shaping our world in significant ways. In developed countries, an aging population with a higher median age is reshaping healthcare systems, retirement policies, and workforce dynamics. Simultaneously, urbanization is accelerating, with over half of the global population now living in cities, presenting challenges and opportunities for infrastructure, resource management, and social development.

Challenges. 1. Overpopulation: Rapid population growth in certain regions can strain resources, leading to issues such as food scarcity, water shortages, and overcrowding. 2. Aging Workforce: As the global population ages, there may be a shortage of skilled workers, affecting economic productivity and social support systems. 3. Environmental Impact: Population growth is closely linked to increased resource consumption and environmental degradation. Sustainable development and conservation efforts are essential to mitigate these effects.

Opportunities. 1. Demographic Dividend: Countries with youthful populations can benefit from a demographic dividend, where a large working-age population can drive economic growth and innovation. 2. Cultural Diversity: A diverse global population can lead to cultural exchange, creativity, and a richer societal tapestry. 3. Innovation and Technology: Addressing the challenges posed by population growth can drive innovation in areas such as healthcare, agriculture, and energy production.

Analysing the world's population is a complex task that involves understanding its growth patterns, demographic shifts, challenges, and opportunities. As the global population continues to rise, it is essential to address the associated challenges while harnessing the potential benefits of a diverse and dynamic world population. Policymakers, researchers, and organizations must work collaboratively to create sustainable solutions that ensure a prosperous future for all.

About this dataset

Context

The dataset tabulates the Los Angeles population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Los Angeles across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Los Angeles was 3.82 million, a 0.05% decrease year-by-year from 2022. Previously, in 2022, Los Angeles population was 3.82 million, a decline of 0.26% compared to a population of 3.83 million in 2021. Over the last 20 plus years, between 2000 and 2023, population of Los Angeles increased by 118,340. In this period, the peak population was 3.98 million in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Los Angeles is shown in this column.
• Year on Year Change: This column displays the change in Los Angeles population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Los Angeles Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Illinois population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Illinois across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2024, the population of Illinois was 12.71 million, a 0.54% increase year-by-year from 2023. Previously, in 2023, Illinois population was 12.64 million, an increase of 0.16% compared to a population of 12.62 million in 2022. Over the last 20 plus years, between 2000 and 2024, population of Illinois increased by 272,590. In this period, the peak population was 12.9 million in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2024

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2024)
• Population: The population for the specific year for the Illinois is shown in this column.
• Year on Year Change: This column displays the change in Illinois population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Illinois Population by Year. You can refer the same here

How many people use social media?

              Social media usage is one of the most popular online activities. In 2024, over five billion people were using social media worldwide, a number projected to increase to over six billion in 2028.

              Who uses social media?
              Social networking is one of the most popular digital activities worldwide and it is no surprise that social networking penetration across all regions is constantly increasing. As of January 2023, the global social media usage rate stood at 59 percent. This figure is anticipated to grow as lesser developed digital markets catch up with other regions
              when it comes to infrastructure development and the availability of cheap mobile devices. In fact, most of social media’s global growth is driven by the increasing usage of mobile devices. Mobile-first market Eastern Asia topped the global ranking of mobile social networking penetration, followed by established digital powerhouses such as the Americas and Northern Europe.

              How much time do people spend on social media?
              Social media is an integral part of daily internet usage. On average, internet users spend 151 minutes per day on social media and messaging apps, an increase of 40 minutes since 2015. On average, internet users in Latin America had the highest average time spent per day on social media.

              What are the most popular social media platforms?
              Market leader Facebook was the first social network to surpass one billion registered accounts and currently boasts approximately 2.9 billion monthly active users, making it the most popular social network worldwide. In June 2023, the top social media apps in the Apple App Store included mobile messaging apps WhatsApp and Telegram Messenger, as well as the ever-popular app version of Facebook.

The total population in the United States was estimated at 341.2 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides - United States Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Population in the world is currently (2020) growing at a rate of around 1.05% per year (down from 1.08% in 2019, 1.10% in 2018, and 1.12% in 2017). The current average population increase is estimated at 81 million people per year. Annual growth rate reached its peak in the late 1960s, when it was at around 2%.

About this dataset

Context

The dataset tabulates the South Carolina population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of South Carolina across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2024, the population of South Carolina was 5.48 million, a 1.69% increase year-by-year from 2023. Previously, in 2023, South Carolina population was 5.39 million, an increase of 1.89% compared to a population of 5.29 million in 2022. Over the last 20 plus years, between 2000 and 2024, population of South Carolina increased by 1.45 million. In this period, the peak population was 5.48 million in the year 2024. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2024

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2024)
• Population: The population for the specific year for the South Carolina is shown in this column.
• Year on Year Change: This column displays the change in South Carolina population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 South Carolina Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Montana population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Montana across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2024, the population of Montana was 1.14 million, a 0.52% increase year-by-year from 2023. Previously, in 2023, Montana population was 1.13 million, an increase of 0.82% compared to a population of 1.12 million in 2022. Over the last 20 plus years, between 2000 and 2024, population of Montana increased by 233,928. In this period, the peak population was 1.14 million in the year 2024. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2024

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2024)
• Population: The population for the specific year for the Montana is shown in this column.
• Year on Year Change: This column displays the change in Montana population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Montana Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Wisconsin population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Wisconsin across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2024, the population of Wisconsin was 5.96 million, a 0.52% increase year-by-year from 2023. Previously, in 2023, Wisconsin population was 5.93 million, an increase of 0.45% compared to a population of 5.9 million in 2022. Over the last 20 plus years, between 2000 and 2024, population of Wisconsin increased by 587,126. In this period, the peak population was 5.96 million in the year 2024. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2024

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2024)
• Population: The population for the specific year for the Wisconsin is shown in this column.
• Year on Year Change: This column displays the change in Wisconsin population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Wisconsin Population by Year. You can refer the same here

The global number of Facebook users was forecast to continuously increase between 2023 and 2027 by in total 391 million users (+14.36 percent). After the fourth consecutive increasing year, the Facebook user base is estimated to reach 3.1 billion users and therefore a new peak in 2027. Notably, the number of Facebook users was continuously increasing over the past years. User figures, shown here regarding the platform Facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.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).

About this dataset

Context

The dataset tabulates the Florida population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Florida across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2024, the population of Florida was 23.37 million, a 2.04% increase year-by-year from 2023. Previously, in 2023, Florida population was 22.9 million, an increase of 2.35% compared to a population of 22.38 million in 2022. Over the last 20 plus years, between 2000 and 2024, population of Florida increased by 7.33 million. In this period, the peak population was 23.37 million in the year 2024. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2024

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2024)
• Population: The population for the specific year for the Florida is shown in this column.
• Year on Year Change: This column displays the change in Florida population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Florida Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Dallas population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Dallas across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Dallas was 1.3 million, a 0.42% increase year-by-year from 2022. Previously, in 2022, Dallas population was 1.3 million, an increase of 0.59% compared to a population of 1.29 million in 2021. Over the last 20 plus years, between 2000 and 2023, population of Dallas increased by 113,194. In this period, the peak population was 1.34 million in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Dallas is shown in this column.
• Year on Year Change: This column displays the change in Dallas population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Dallas Population by Year. 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.

Community science image libraries offer a massive, but largely untapped, source of observational data for phenological research. The iNaturalist platform offers a particularly rich archive, containing more than 49 million verifiable, georeferenced, open access images, encompassing seven continents and over 278,000 species. A critical limitation preventing scientists from taking full advantage of this rich data source is labor. Each image must be manually inspected and categorized by phenophase, which is both time-intensive and costly. Consequently, researchers may only be able to use a subset of the total number of images available in the database. While iNaturalist has the potential to yield enough data for high-resolution and spatially extensive studies, it requires more efficient tools for phenological data extraction. A promising solution is automation of the image annotation process using deep learning. Recent innovations in deep learning have made these open-source tools accessible to a general research audience. However, it is unknown whether deep learning tools can accurately and efficiently annotate phenophases in community science images. Here, we train a convolutional neural network (CNN) to annotate images of Alliaria petiolata into distinct phenophases from iNaturalist and compare the performance of the model with non-expert human annotators. We demonstrate that researchers can successfully employ deep learning techniques to extract phenological information from community science images. A CNN classified two-stage phenology (flowering and non-flowering) with 95.9% accuracy and classified four-stage phenology (vegetative, budding, flowering, and fruiting) with 86.4% accuracy. The overall accuracy of the CNN did not differ from humans (p = 0.383), although performance varied across phenophases. We found that a primary challenge of using deep learning for image annotation was not related to the model itself, but instead in the quality of the community science images. Up to 4% of A. petiolata images in iNaturalist were taken from an improper distance, were physically manipulated, or were digitally altered, which limited both human and machine annotators in accurately classifying phenology. Thus, we provide a list of photography guidelines that could be included in community science platforms to inform community scientists in the best practices for creating images that facilitate phenological analysis.

Methods Creating a training and validation image set

We downloaded 40,761 research-grade observations of A. petiolata from iNaturalist, ranging from 1995 to 2020. Observations on the iNaturalist platform are considered “research-grade if the observation is verifiable (includes image), includes the date and location observed, is growing wild (i.e. not cultivated), and at least two-thirds of community users agree on the species identification. From this dataset, we used a subset of images for model training. The total number of observations in the iNaturalist dataset are heavily skewed towards more recent years. Less than 5% of the images we downloaded (n=1,790) were uploaded between 1995-2016, while over 50% of the images were uploaded in 2020. To mitigate temporal bias, we used all available images between the years 1995 and 2016 and we randomly selected images uploaded between 2017-2020. We restricted the number of randomly-selected images in 2020 by capping the number of 2020 images to approximately the number of 2019 observations in the training set. The annotated observation records are available in the supplement (supplementary data sheet 1). The majority of the unprocessed records (those which hold a CC-BY-NC license) are also available on GBIF.org (2021).

One of us (R. Reeb) annotated the phenology of training and validation set images using two different classification schemes: two-stage (non-flowering, flowering) and four-stage (vegetative, budding, flowering, fruiting). For the two-stage scheme, we classified 12,277 images and designated images as ‘flowering’ if there was one or more open flowers on the plant. All other images were classified as non-flowering. For the four-stage scheme, we classified 12,758 images. We classified images as ‘vegetative’ if no reproductive parts were present, ‘budding’ if one or more unopened flower buds were present, ‘flowering’ if at least one opened flower was present, and ‘fruiting’ if at least one fully-formed fruit was present (with no remaining flower petals attached at the base). Phenology categories were discrete; if there was more than one type of reproductive organ on the plant, the image was labeled based on the latest phenophase (e.g. if both flowers and fruits were present, the image was classified as fruiting).

For both classification schemes, we only included images in the model training and validation dataset if the image contained one or more plants with clearly visible reproductive parts were clear and we could exclude the possibility of a later phenophase. We removed 1.6% of images from the two-stage dataset that did not meet this requirement, leaving us with a total of 12,077 images, and 4.0% of the images from the four-stage leaving us with a total of 12,237 images. We then split the two-stage and four-stage datasets into a model training dataset (80% of each dataset) and a validation dataset (20% of each dataset).

Training a two-stage and four-stage CNN

We adapted techniques from studies applying machine learning to herbarium specimens for use with community science images (Lorieul et al. 2019; Pearson et al. 2020). We used transfer learning to speed up training of the model and reduce the size requirements for our labeled dataset. This approach uses a model that has been pre-trained using a large dataset and so is already competent at basic tasks such as detecting lines and shapes in images. We trained a neural network (ResNet-18) using the Pytorch machine learning library (Psake et al. 2019) within Python. We chose the ResNet-18 neural network because it had fewer convolutional layers and thus was less computationally intensive than pre-trained neural networks with more layers. In early testing we reached desired accuracy with the two-stage model using ResNet-18. ResNet-18 was pre-trained using the ImageNet dataset, which has 1,281,167 images for training (Deng et al. 2009). We utilized default parameters for batch size (4), learning rate (0.001), optimizer (stochastic gradient descent), and loss function (cross entropy loss). Because this led to satisfactory performance, we did not further investigate hyperparameters.

Because the ImageNet dataset has 1,000 classes while our data was labeled with either 2 or 4 classes, we replaced the final fully-connected layer of the ResNet-18 architecture with fully-connected layers containing an output size of 2 for the 2-class problem and 4 for the 4-class problem. We resized and cropped the images to fit ResNet’s input size of 224x224 pixels and normalized the distribution of the RGB values in each image to a mean of zero and a standard deviation of one, to simplify model calculations. During training, the CNN makes predictions on the labeled data from the training set and calculates a loss parameter that quantifies the model’s inaccuracy. The slope of the loss in relation to model parameters is found and then the model parameters are updated to minimize the loss value. After this training step, model performance is estimated by making predictions on the validation dataset. The model is not updated during this process, so that the validation data remains ‘unseen’ by the model (Rawat and Wang 2017; Tetko et al. 1995). This cycle is repeated until the desired level of accuracy is reached. We trained our model for 25 of these cycles, or epochs. We stopped training at 25 epochs to prevent overfitting, where the model becomes trained too specifically for the training images and begins to lose accuracy on images in the validation dataset (Tetko et al. 1995).

We evaluated model accuracy and created confusion matrices using the model’s predictions on the labeled validation data. This allowed us to evaluate the model’s accuracy and which specific categories are the most difficult for the model to distinguish. For using the model to make phenology predictions on the full, 40,761 image dataset, we created a custom dataloader function in Pytorch using the Custom Dataset function, which would allow for loading images listed in a csv and passing them through the model associated with unique image IDs.

Hardware information

Model training was conducted using a personal laptop (Ryzen 5 3500U cpu and 8 GB of memory) and a desktop computer (Ryzen 5 3600 cpu, NVIDIA RTX 3070 GPU and 16 GB of memory).

Comparing CNN accuracy to human annotation accuracy

We compared the accuracy of the trained CNN to the accuracy of seven inexperienced human scorers annotating a random subsample of 250 images from the full, 40,761 image dataset. An expert annotator (R. Reeb, who has over a year’s experience in annotating A. petiolata phenology) first classified the subsample images using the four-stage phenology classification scheme (vegetative, budding, flowering, fruiting). Nine images could not be classified for phenology and were removed. Next, seven non-expert annotators classified the 241 subsample images using an identical protocol. This group represented a variety of different levels of familiarity with A. petiolata phenology, ranging from no research experience to extensive research experience (two or more years working with this species). However, no one in the group had substantial experience classifying community science images and all were naïve to the four-stage phenology scoring protocol. The trained CNN was also used to classify the subsample images. We compared human annotation accuracy in each phenophase to the accuracy of the CNN using students

About this dataset

Context

The dataset tabulates the Phoenix population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Phoenix across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Phoenix was 1.65 million, a 0.38% increase year-by-year from 2022. Previously, in 2022, Phoenix population was 1.64 million, an increase of 1.15% compared to a population of 1.63 million in 2021. Over the last 20 plus years, between 2000 and 2023, population of Phoenix increased by 322,874. In this period, the peak population was 1.68 million in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Phoenix is shown in this column.
• Year on Year Change: This column displays the change in Phoenix population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Phoenix Population by Year. You can refer the same here