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.

Until the 1800s, population growth was incredibly slow on a global level. The global population was estimated to have been around 188 million people in the year 1CE, and did not reach one billion until around 1803. However, since the 1800s, a phenomenon known as the demographic transition has seen population growth skyrocket, reaching eight billion people in 2023, and this is expected to peak at over 10 billion in the 2080s.

Chad TD: Population in Urban Agglomerations of More Than 1 Million data was reported at 1,655,618.000 Person in 2024. This records an increase from the previous number of 1,592,324.000 Person for 2023. Chad TD: Population in Urban Agglomerations of More Than 1 Million data is updated yearly, averaging 515,373.000 Person from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 1,655,618.000 Person in 2024 and a record low of 71,280.000 Person in 1960. Chad TD: Population in Urban Agglomerations of More Than 1 Million data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank.WDI: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the country's population living in metropolitan areas that in 2018 had a population of more than one million people.;United Nations, World Urbanization Prospects.;;

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.

Chad TD: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data was reported at 8.156 % in 2024. This records a decrease from the previous number of 8.242 % for 2023. Chad TD: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data is updated yearly, averaging 7.989 % from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 8.304 % in 2022 and a record low of 2.337 % in 1960. Chad TD: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank.WDI: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the percentage of a country's population living in metropolitan areas that in 2018 had a population of more than one million people.;United Nations, World Urbanization Prospects.;Weighted average;

Mali ML: Population in Urban Agglomerations of More Than 1 Million data was reported at 2,368,347.000 Person in 2017. This records an increase from the previous number of 2,292,458.000 Person for 2016. Mali ML: Population in Urban Agglomerations of More Than 1 Million data is updated yearly, averaging 703,465.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2,368,347.000 Person in 2017 and a record low of 130,017.000 Person in 1960. Mali ML: Population in Urban Agglomerations of More Than 1 Million data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the country's population living in metropolitan areas that in 2018 had a population of more than one million people.; ; United Nations, World Urbanization Prospects.; ;

Austria AT: Population in Urban Agglomerations of More Than 1 Million data was reported at 1,990,487.000 Person in 2024. This records an increase from the previous number of 1,975,271.000 Person for 2023. Austria AT: Population in Urban Agglomerations of More Than 1 Million data is updated yearly, averaging 1,618,539.000 Person from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 1,990,487.000 Person in 2024 and a record low of 1,531,462.000 Person in 1981. Austria AT: Population in Urban Agglomerations of More Than 1 Million data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Austria – Table AT.World Bank.WDI: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the country's population living in metropolitan areas that in 2018 had a population of more than one million people.;United Nations, World Urbanization Prospects.;;

The USGS’s FORE-SCE model was used to produce unprecedented landscape projections for the Prairie Potholes region of the northern Great Plains of the United States. The projections are characterized by 1) high spatial resolution (30-meter cells), 2) high thematic resolution (29 land use and land cover classes), 3) broad spatial extent (covering much of the Great Plains), 4) use of real land ownership boundaries to ensure realistic representation of landscape patterns, and 5) representation of both anthropogenic land use and natural vegetation change. A variety of scenarios were modeled from 2014 to 2100, with decadal timesteps (i.e., 2014, 2020, 2030, etc.). Modeled land use and natural vegetation classes were responsive to projected future changes in environmental conditions, including changes in groundwater and water access. Eleven primary land-use scenarios were modeled, from four different scenario families. The land-use scenarios focused on socioeconomic impacts on anthropogenic land use (demographics, energy use, agricultural economics, and other socioeconomic considerations). The following provides a brief summary of the 11 major land-use scenarios. 1) Business-as-usual - Based on an extrapolation of recent land-cover trends as derived from remote-sensing data. Overall trends were provided by 2001 to 2011 change in the National Land Cover Database, while change in crop types were extrapolated from 2008 to 2014 change in the Cropland Data Layer. Overall the scenario is marked by expansion of high-value traditional crops (corn, soybeans, cotton), with a concurrent decline in dryland wheat and some other lower-value crops. 2) Billion Ton Update scenario ($40 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update (BTU). The $40 scenario represents likely agricultural conditions under an assumed farmgate price of $40 per dry ton of biomass (for the production of biofuel). This is the least aggressive BTU scenario for placing "perennial grass" (for biofuel feedstock) on the landscape. 3) Billion Ton Update scenario ($60 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $60 scenario represents likely agricultural conditions under an assumed farmgate price of $60 per dry ton of biomass (for the production of biofuel). At the higher farmgate price, the perennial grass class expands dramatically. 4) Billion Ton Update scenario ($80 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $80 scenario represents likely agricultural conditions under an assumed farmgate price of $80 per dry ton of biomass (for the production of biofuel). With the high farmgate price, this scenario shows the highest expansion of perennial grass among the 11 modeled scenarios. 5) GCAM Reference scenario - Based on global-scale scenarios from the GCAM model, the "reference" scenario provides a likely landscape under a world without specific carbon or climate mitigation efforts. As such, it's another form of a "business-as-usual" scenario. 6) GCAM 4.5 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 4.5 model represents a mid-level mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of ~4.5 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland (including perennial grass used as feedstock for cellulosic biofuel production). 7) GCAM 2.6 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 2.6 model represents a very aggressive mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of only ~2.6 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland (including perennial grass used as feedstock for cellulosic biofuel production). 8) SRES A1B scenario - A scenario consistent with the Intergovernmental Panel on Climate Change (IPCC's) Special Report on Emissions Scenarios (SRES) A1B storyline. In the A1B scenario, economic activity is prioritized over environmental conservation. Agriculture expands substantially, including use of perennial grasses for biofuel production. 9) SRES A2 scenario - A scenario consistent with the IPCC's SRES A2 storyline. In the A2 scenario, global population levels reach 15 billion by 2100. Economic activity is prioritized over environmental conservation. This scenario has the highest overall expansion of traditional cropland, given the very high demand for foodstuffs and other agricultural commodities. 10) SRES B1 scenario - A scenario consistent with the IPCC's SRES B1 storyline. In the B1 scenario, environmental conservation is valued, as is regional cooperation. Much less agricultural expansion occurs as compared to the A1B or A2 scenarios. 11) SRES B2 scenario - A scenario consistent with the IPCC's SRES B2 storyline. In the B2 scenario, environmental conservation is highly valued. Of the eleven modeled scenarios, the B2 scenarios has the smallest overall agricultural footprint (traditional cropland, hay/pasture, perennial grasses). For each of the eleven land-use scenarios, three alternative climate / vegetation scenarios were modeled, resulting in 33 unique scenario combinations. The alternative vegetation scenarios represent the potential changes in quantity and distribution of the major vegetation classes that were modeled (grassland, shrubland, deciduous forest, mixed forest, and evergreen forest), as a response to potential future climate conditions. The three alternative vegetation scenarios correspond to climate conditions consistent with 1) The Intergovernmental Panel on Climate Change (IPCC's) Representative Concentration Pathway (RCP) 8.5 scenario (a scenario of high climate change), 2) the RCP 4.5 scenario (a mid-level climate change scenario), and 3) a mid-point climate that averages RCP4.5 and RCP8.5 conditions Data are provided here for each of the 33 possible scenario combinations. Each scenario file is provided as a zip file containing 1) starting 2014 land cover for the region, and 2) decadal timesteps of modeled land-cover from 2020 through 2100. The "attributes" section of the metadata provides a key for identifying file names associated with each of the 33 scenario combinations.

Some say climate change is the biggest threat of our age while others say it’s a myth based on dodgy science. We are turning some of the data over to you so you can form your own view.

Even more than with other data sets that Kaggle has featured, there’s a huge amount of data cleaning and preparation that goes into putting together a long-time study of climate trends. Early data was collected by technicians using mercury thermometers, where any variation in the visit time impacted measurements. In the 1940s, the construction of airports caused many weather stations to be moved. In the 1980s, there was a move to electronic thermometers that are said to have a cooling bias.

Given this complexity, there are a range of organizations that collate climate trends data. The three most cited land and ocean temperature data sets are NOAA’s MLOST, NASA’s GISTEMP and the UK’s HadCrut.

We have repackaged the data from a newer compilation put together by the Berkeley Earth, which is affiliated with Lawrence Berkeley National Laboratory. The Berkeley Earth Surface Temperature Study combines 1.6 billion temperature reports from 16 pre-existing archives. It is nicely packaged and allows for slicing into interesting subsets (for example by country). They publish the source data and the code for the transformations they applied. They also use methods that allow weather observations from shorter time series to be included, meaning fewer observations need to be thrown away.

In this dataset, we have include several files:

Global Land and Ocean-and-Land Temperatures (GlobalTemperatures.csv):

• Date: starts in 1750 for average land temperature and 1850 for max and min land temperatures and global ocean and land temperatures
• LandAverageTemperature: global average land temperature in celsius
• LandAverageTemperatureUncertainty: the 95% confidence interval around the average
• LandMaxTemperature: global average maximum land temperature in celsius
• LandMaxTemperatureUncertainty: the 95% confidence interval around the maximum land temperature
• LandMinTemperature: global average minimum land temperature in celsius
• LandMinTemperatureUncertainty: the 95% confidence interval around the minimum land temperature
• LandAndOceanAverageTemperature: global average land and ocean temperature in celsius
• LandAndOceanAverageTemperatureUncertainty: the 95% confidence interval around the global average land and ocean temperature

Other files include:

• Global Average Land Temperature by Country (GlobalLandTemperaturesByCountry.csv)
• Global Average Land Temperature by State (GlobalLandTemperaturesByState.csv)
• Global Land Temperatures By Major City (GlobalLandTemperaturesByMajorCity.csv)
• Global Land Temperatures By City (GlobalLandTemperaturesByCity.csv)

The raw data comes from the Berkeley Earth data page.

Somalia SO: Population in Urban Agglomerations of More Than 1 Million data was reported at 2,393,603.000 Person in 2017. This records an increase from the previous number of 2,264,850.000 Person for 2016. Somalia SO: Population in Urban Agglomerations of More Than 1 Million data is updated yearly, averaging 939,327.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2,393,603.000 Person in 2017 and a record low of 93,923.000 Person in 1960. Somalia SO: Population in Urban Agglomerations of More Than 1 Million data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Somalia – Table SO.World Bank: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the country's population living in metropolitan areas that in 2000 had a population of more than one million people.; ; United Nations, World Urbanization Prospects.; ;

The urban–rural continuum classifies the global population, allocating rural populations around differently-sized cities. The classification is based on four dimensions: population distribution, population density, urban center location, and travel time to urban centers, all of which can be mapped globally and consistently and then aggregated as administrative unit statistics.Using spatial data, we matched all rural locations to their urban center of reference based on the time needed to reach these urban centers. A hierarchy of urban centers by population size (largest to smallest) is used to determine which center is the point of “reference” for a given rural location: proximity to a larger center “dominates” over a smaller one in the same travel time category. This was done for 7 urban categories and then aggregated, for presentation purposes, into “large cities” (over 1 million people), “intermediate cities” (250,000 –1 million), and “small cities and towns” (20,000–250,000).Finally, to reflect the diversity of population density across the urban–rural continuum, we distinguished between high-density rural areas with over 1,500 inhabitants per km2 and lower density areas. Unlike traditional functional area approaches, our approach does not define urban catchment areas by using thresholds, such as proportion of people commuting; instead, these emerge endogenously from our urban hierarchy and by calculating the shortest travel time.Urban-Rural Catchment Areas (URCA).tif is a raster dataset of the 30 urban–rural continuum categories for the urban–rural continuum showing the catchment areas around cities and towns of different sizes. Each rural pixel is assigned to one defined travel time category: less than one hour, one to two hours, and two to three hours travel time to one of seven urban agglomeration sizes. The agglomerations range from large cities with i) populations greater than 5 million and ii) between 1 to 5 million; intermediate cities with iii) 500,000 to 1 million and iv) 250,000 to 500,000 inhabitants; small cities with populations v) between 100,000 and 250,000 and vi) between 50,000 and 100,000; and vii) towns of between 20,000 and 50,000 people. The remaining pixels that are more than 3 hours away from any urban agglomeration of at least 20,000 people are considered as either hinterland or dispersed towns being that they are not gravitating around any urban agglomeration. The raster also allows for visualizing a simplified continuum created by grouping the seven urban agglomerations into 4 categories.Urban-Rural Catchment Areas (URCA).tif is in GeoTIFF format, band interleaved with LZW compression, suitable for use in Geographic Information Systems and statistical packages. The data type is byte, with pixel values ranging from 1 to 30. The no data value is 128. It has a spatial resolution of 30 arc seconds, which is approximately 1km at the equator. The spatial reference system (projection) is EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long). The geographic extent is 83.6N - 60S / 180E - 180W. The same tif file is also available as an ESRI ArcMap MapPackage Urban-Rural Catchment Areas.mpkFurther details are in the ReadMe_data_description.docx

Haiti HT: Population in Urban Agglomerations of More Than 1 Million data was reported at 2,579,002.000 Person in 2017. This records an increase from the previous number of 2,507,309.000 Person for 2016. Haiti HT: Population in Urban Agglomerations of More Than 1 Million data is updated yearly, averaging 1,051,786.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2,642,763.000 Person in 2009 and a record low of 247,495.000 Person in 1960. Haiti HT: Population in Urban Agglomerations of More Than 1 Million data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Haiti – Table HT.World Bank: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the country's population living in metropolitan areas that in 2000 had a population of more than one million people.; ; United Nations, World Urbanization Prospects.; ;

Haiti HT: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data was reported at 23.486 % in 2017. This records an increase from the previous number of 23.115 % for 2016. Haiti HT: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data is updated yearly, averaging 15.275 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 26.822 % in 2009 and a record low of 6.402 % in 1960. Haiti HT: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Haiti – Table HT.World Bank: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the percentage of a country's population living in metropolitan areas that in 2000 had a population of more than one million people.; ; United Nations, World Urbanization Prospects.; Weighted Average;

Ghana GH: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data was reported at 18.366 % in 2017. This records an increase from the previous number of 18.068 % for 2016. Ghana GH: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data is updated yearly, averaging 12.680 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 18.366 % in 2017 and a record low of 9.224 % in 1960. Ghana GH: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ghana – Table GH.World Bank.WDI: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the percentage of a country's population living in metropolitan areas that in 2018 had a population of more than one million people.; ; United Nations, World Urbanization Prospects.; Weighted average;

Paraguay PY: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data was reported at 46.026 % in 2017. This records an increase from the previous number of 45.352 % for 2016. Paraguay PY: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data is updated yearly, averaging 25.797 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 46.026 % in 2017 and a record low of 20.230 % in 1960. Paraguay PY: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Paraguay – Table PY.World Bank.WDI: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the percentage of a country's population living in metropolitan areas that in 2018 had a population of more than one million people.; ; United Nations, World Urbanization Prospects.; Weighted average;

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Climate change is expected to hit developing countries the hardest. Its effects—higher temperatures, changes in precipitation patterns, rising sea levels, and more frequent weather-related disasters—pose risks for agriculture, food, and water supplies. At stake are recent gains in the fight against poverty, hunger and disease, and the lives and livelihoods of billions of people in developing countries. Addressing climate change requires unprecedented global cooperation across borders. The World Bank Group is helping support developing countries and contributing to a global solution, while tailoring our approach to the differing needs of developing country partners. Data here cover climate systems, exposure to climate impacts, resilience, greenhouse gas emissions, and energy use. Other indicators relevant to climate change are found under other data pages, particularly Environment, Agriculture & Rural Development, Energy & Mining, Health, Infrastructure, Poverty, and Urban Development. Indicators: Access to electricity, Agricultural irrigated land, Agricultural land, Agriculture, Annual freshwater withdrawals, Arable land, Average precipitation in depth, CO2 emissions, CO2 emissions from gaseous fuel consumption, CO2 emissions from liquid fuel consumption, CO2 emissions from solid fuel consumption, CO2 intensity, CPIA public sector management and institutions cluster average, Cereal yield, Community health workers, Disaster risk reduction progress score, Droughts, Ease of doing business index, Electric power consumption, Electricity production from coal sources, Electricity production from hydroelectric sources, Electricity production from natural gas sources, Electricity production from nuclear sources, Electricity production from oil sources, Electricity production from renewable sources, Energy use, Foreign direct investment, Forest area, GHG net emissions/removals by LUCF, HFC gas emissions, Land area where elevation is below 5 meters, Marine protected areas, Methane emissions, Mortality rate, Nitrous oxide emissions, Other greenhouse gas emissions, PFC gas emissions, Population, Population growth, Population in urban agglomerations of more than 1 million, Population living in areas where elevation is below 5 meters, Poverty headcount ratio at $1.90 a day, Prevalence of underweight, Primary completion rate, Renewable electricity output, Renewable energy consumption, Rural land area where elevation is below 5 meters, Rural population living in areas where elevation is below 5 meters, SF6 gas emissions, School enrollment, Terrestrial and marine protected areas, Terrestrial protected areas, Total greenhouse gas emissions, Urban land area where elevation is below 5 meters, Urban population, Urban population growth, Urban population living in areas where elevation is below 5 meters

Senegal SN: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data was reported at 23.922 % in 2017. This records an increase from the previous number of 23.703 % for 2016. Senegal SN: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data is updated yearly, averaging 18.420 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 23.922 % in 2017 and a record low of 11.198 % in 1960. Senegal SN: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Senegal – Table SN.World Bank: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the percentage of a country's population living in metropolitan areas that in 2000 had a population of more than one million people.; ; United Nations, World Urbanization Prospects.; Weighted Average;

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).

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.

The global number of internet users in was forecast to continuously increase between 2024 and 2029 by in total 1.3 billion users (+23.66 percent). After the fifteenth consecutive increasing year, the number of users is estimated to reach 7 billion users and therefore a new peak in 2029. Notably, the number of internet users of was continuously increasing over the past years.Depicted is the estimated number of individuals in the country or region at hand, that use the internet. As the datasource clarifies, connection quality and usage frequency are distinct aspects, not taken into account here.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).Find more key insights for the number of internet users in countries like the Americas and Asia.