Which county has the most Facebook users? There are more than 383 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 196.9 million, 122.3 million, and 111.65 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.

This layer shows the market potential that an adult has visited facebook.com in the last 30 days in the U.S. in 2016 in a multiscale map (by country, state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Market Potential Index and count of adults expected to visit FacebookMarket Potential Index and count of adults expected to visit various social media websitesMarket Potential Index and count of adults expected to visit various news websitesEsri's 2016 Market Potential (MPI) data measures the likely demand for a product or service in an area. The database includes an expected number of consumers and a Market Potential Index (MPI) for each product or service. An MPI compares the demand for a specific product or service in an area with the national demand for that product or service. The MPI values at the US level are 100, representing average demand for the country. A value of more than 100 represents higher demand than the national average, and a value of less than 100 represents lower demand than the national average. For example, an index of 120 implies that demand in the area is 20 percent higher than the US average; an index of 80 implies that demand is 20 percent lower than the US average. See Market Potential database to view the methodology statement and complete variable list.Esri's Electronics & Internet Data Collection includes data that measures the likely demand for electronics and internet usage. The database includes an expected number of consumers and a Market Potential Index (MPI) for each product, activity, or service. See the United States Data Browser to view complete variable lists for each Esri demographics collection.Additional Esri Resources:U.S. 2016/2021 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layers

Population data for a selection of countries, allocated to 1 arcsecond blocks and provided in a combination of CSV and Cloud-optimized GeoTIFF files. This refines CIESIN’s Gridded Population of the World using machine learning models on high-resolution worldwide Maxar satellite imagery. CIESIN population counts aggregated from worldwide census data are allocated to blocks where imagery appears to contain buildings.

This map is part of SDGs Today. Please see sdgstoday.orgTo ensure that all women and girls can benefit from the digital revolution, tracking progress on gender inequalities in relation to internet and mobile access and use is more important than ever. Unfortunately, the data are significantly lacking in geographic coverage, comparability, and timeliness. The University of Oxford and Qatar Computing Research Institute (QCRI), with support from Data2X, are collaborating to measure digital gender gaps in real time. The Digital Gender Gaps project uses Facebook marketing data to generate a country-level dataset combining ‘online’ indicators of Facebook users by gender, age, and device type. These online indicators are used to predict internet and mobile use gender gaps by validating them against data on gender gaps in internet and mobile access from nationally-representative surveys where available. The data shows the internet gender gap (ratio of female-to-male internet use) and mobile gender gap (female-to-male mobile use) estimated using the Facebook Gender Gap Index (female-to-male ratio of Facebook users).Read more about the methodology here. To learn more about the project visit www.digitalgendergaps.org. Contact Ridhi Kashyap (ridhi.kashyap@nuffield.ox.ac.uk) or Ingmar Weber (iweber@hbku.edu.qa) for any questions about the data.

This web map presents a vector basemap of OpenStreetMap (OSM) data hosted by Esri. Esri created this vector tile basemap from the Daylight map distribution of OSM data, which is supported by Facebook and supplemented with additional data from Microsoft. This version of the map is rendered using OSM cartography. The OSM Daylight map will be updated every month with the latest version of OSM Daylight data.OpenStreetMap is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site:www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this enhanced vector basemap available to the ArcGIS user and developer communities.

Global and regional Canopy Height Maps (CHM). Created using machine learning models on high-resolution worldwide Maxar satellite imagery.

UNCLASSIFIEDInternet cafés are difficult to identify in Gabon, given limited advertising and the ease with which proprietors operate from small, non-descript locations. As such, the country contained upwards of 200 internet cafés in 2005, of which 90 percent were located in Libreville. Though fixed-line internet infrastructure has expanded dramatically over the last decade, Gabon’s limited fiber-optic connectivity and high access prices have allowed mobile networks to leap-frog the fixed internet market. The mobile segment accounted for 94% of the country’s total internet users by the end of 2013, despite providers’ reliance on slower connection speeds. Continued growth in mobile markets in 2014 (pursuant form the recent initiation of 3G services), may inhibit the popularity and growth of cyber cafés, particularly in the near term. Looking further afield, the Gabonese government’s 2012 signature of a loan agreement with the World Bank will afford the country access to the Africa Coast to Europe (ACE) submarine cable, a fiber optic infrastructure project to improve connectivity for all participating countries. Enhanced connection speeds and reductions in fixed-line access costs pursuant from the project’s completion may surge the number of cyber cafés in the country.Attribute Table Field DescriptionsISO3-International Organization for Standardization 3-digit country codeADM0_NAME-Administration level zero identification / nameADM1_NAME-Administration level one identification / nameADM2_NAME-Administration level two identification / nameNAME-Name of internet caféCITY-City location availableSPA_ACC-Spatial accuracy of site location (1 – high, 2 – medium, 3 – low)COMMENTS-Comments or notes regarding the internet caféSOURCE_DT-Source one creation dateSOURCE-Source oneSOURCE2_DT-Source two creation dateSOURCE2-Source twoCollectionThe feature class was generated utilizing data from OpenStreetMap, Google, and other sources. OpenStreetMap is a free worldwide map, created by crowd-sourcing. Consistent naming conventions for geographic locations were attempted but name variants may exist, which can include historical or less widespread interpretations.The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe is not responsible for the accuracy and completeness of data compiled from outside sources.Sources (HGIS)“Club Afrique.” World66. January 2014. Accessed December 02, 2014.“Codiservices.” Facebook. February 19, 2014. Accessed December 02, 2014. http://www.facebook.com.“DigitalGlobe Imagery Archive.” DigitalGlobe. Accessed December 02, 2014. “Gabon: Internet Cafés.” Yellow Pages. 2014. Accessed December 02, 2014. http://www.gabon.yellowpg.com.“Gabon.” OpenStreetMap. September 2014. Accessed December 02, 2014. http://www.openstreetmap.org.Google. December 2014. Accessed December 02, 2014. http://www.google.com.“Internet Café in Gabon.” Cybo. January 2014. Accessed December 03, 2014. http://www.cybo.com.“Le Meridien Mandji.” Expedia. January 2014. Accessed December 03, 2014. http://www.expedia.fr.Modandi, Moses. “Development of the mobile telephony and social link in Africa: the case of Gabon.” University of Lyon. December 09, 2005. Accessed December 02, 2014. http://www.theses.univ-lyon2.fr.“Ntic Services & Trading Cyber Café.” Facebook. May 13, 2013. Accessed December 02, 2014. http://www.facebook.com.Sources (Metadata)“Airtel Gabon wins 3G License.” TeleGeography. October 11, 2011. Accessed November 19, 2014. http://www.telegeogrpahy.com. “Freedom of the Press: Gabon.” Freedom House. 2014. Accessed November 19, 2014. http://www.freedomhouse.org.“Gabon Media Stats.” NationMaster. 2014. Accessed November 19, 2014. http://www.nationmaster.com.“Gabon – Telecoms, Mobile and Broadband – Market Insights and Statistics.” BuddeComm. December 2013. Accessed November 19, 2014. http://www.budde.com.au."ITU ICT EYE: Gabon." International Telecommunication Union. January 2014. Accessed November 19, 2014. http://www.itu.int.“The Report: Gabon 2014.” Oxford Business Group. 2014. Accessed December 03, 2014. http://www.oxfordbusinessgroup.com.“World Development Indicators.” The World Bank Group. January 2014. Accessed November 19, 2014. http://www.data.worldbank.org.UNCLASSIFIED

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

Overview:

Global results from gridfinder model, produced by ESMAP based on joint work with Facebook and others. Uses night-time lights, road networks and existing grid network data to predict the location of transmission and distribution lines globally. Validated in several countries with ~70% accuracy at 1 km.

More information:

Blog with brief overview: https://blogs.worldbank.org/energy/using-night-lights-map-electrical-gri...
Full research paper: https://www.nature.com/articles/s41597-019-0347-4
Visualization: https://gridfinder.org/

The following data are included:

• grid.gpkg: Vectorized predicted distribution and transmission line network, with existing OpenStreetMap lines tagged in the 'source' column
• targets.tif: Binary raster showing locations predicted to be connected to distribution grid.
• lv.tif: Raster of predicted low-voltage infrastructure in kilometres per cell.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

As of February 2025, India had a total of 413.85 million Instagram users, the largest Instagram audience in the world. The United States had 171.7 million users, and Brazil had 140.7 million. Indonesia, Turkey, and Japan ranked in fourth, fifth and sixth position, respectively. Kazakhstan is the leading country for Instagram audience reach, with 86.2 percent of the population using the social media service. Turkey came in second, with a penetration rate of 85.5 percent and Uruguay ranked third, with 87.1 percent, followed closely by the UAE, Brazil, and Bahrain. It took Instagram 11.2 years to reach the milestone of 2 billion monthly active users worldwide. WhatsApp, also owned by Meta, took 11 years, whilst Facebook took 13.3 years and YouTube took just over 14 years. Instagram’s demographics in the United States As of March 2025, Instagram was the fourth most visited social media service in the United States, after Facebook, Pinterest and X. Out of TikTok, Instagram and Snapchat, TikTok was the most used of all three platforms by Generation Z. Overall, 57 percent of Gen Z social media users used Instagram in 2021, down from 61 percent in 2020 and 64 percent in 2019. Instagram finds most popularity with those in the 25 to 34 year age group, and as of January 2025, roughly 28.3 of all users in the United States belonged to this age group. The social media app was also more likely to be used by women. Most followed accounts on Instagram Instagram’s official account had the most followers as of April 2024 with over 672 million followers. Manchester United forward Cristiano Ronaldo (@cristiano) had over 628 million followers on the platform, while the Argentinian footballer Lionel Messi (@leomessi) had over 502 million followers. The Instagram accounts of the American singer and actress Selena Gomez (@selenagomez) and the media personality and makeup mogul Kylie Jenner (@kyliejenner) had over 400 million followers each.

Mature Support Notice: This item is in mature support as of December 2024. See blog for more information.This app features a vector basemap of OpenStreetMap (OSM) data hosted by Esri. Esri created this vector tile basemap from the Daylight map distribution of OSM data, which is supported by Facebook and supplemented with additional data from Microsoft. This version of the map is rendered using OSM cartography. OpenStreetMap is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this enhanced vector basemap available to the ArcGIS user and developer communities.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

VERSION 1.5. The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Nigeria: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Methodology

These high-resolution maps are created using machine learning techniques to identify buildings from commercially available satellite images. This is then overlayed with general population estimates based on publicly available census data and other population statistics at Columbia University. The resulting maps are the most detailed and actionable tools available for aid and research organizations. For more information about the methodology used to create our high resolution population density maps and the demographic distributions, click [here](https://dataforgood.fb.com/docs/methodology-high-resolution-population-density-maps-demographic-estimates/

For information about how to use HDX to access these datasets, please visit: https://dataforgood.fb.com/docs/high-resolution-population-density-maps-demographic-estimates-documentation/

Adjustments to match the census population with the UN estimates are applied at the national level. The UN estimate for a given country (or state/territory) is divided by the total census estimate of population for the given country. The resulting adjustment factor is multiplied by each administrative unit census value for the target year. This preserves the relative population totals across administrative units while matching the UN total. More information can be found here

Elevate your B2B marketing strategy with B2B Email Databases' premier Google Maps Data Extraction Service. Our cutting-edge solution offers direct access to a wealth of business information from Google's extensive database, encompassing millions of businesses across a multitude of industries worldwide.

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The dataset is a zip file that contains 28 cloud optimized tiff files that cover the continent of Africa. Each of the 28 files represents a region or area - these are not divided by country. These 28 tiff files represent 2015 population estimates. However, please note that many of the country-level files include 2020 population estimates including: Angola, Benin, Botswana, Burundi, Cameroon, Cabo Verde, Cote d'Ivoire, Djibouti, Eritrea, Eswatini, The Gambia, Ghana, Lesotho, Liberia, Mozambique, Namibia, Sao Tome & Principe, Sierra Leone, South Africa, Togo, Zambia, and Zimbabwe. To create the high-resolution maps, machine learning techniques are used to identify buildings from commercially available satellite images then general population estimates are overlaid based on publicly available census data and other population statistics. The resulting maps are the most detailed and actionable tools available for aid and research organizations.

Facebook has produced a model to help map global medium voltage (MV) grid infrastructure, i.e. the distribution lines which connect high-voltage transmission infrastructure to consumer-serving low-voltage distribution. The data found here are model outputs for six select African countries: Malawi, Nigeria, Uganda, DRC, Cote D’Ivoire, and Zambia. The grid maps are produced using a new methodology that employs various publicly-available datasets (night time satellite imagery, roads, political boundaries, etc) to predict the location of existing MV grid infrastructure. The model documentation and code are also available , so data scientists and planners globally can replicate the model to expand model coverage to other countries where this data is not already available. You can find the model code and documentation here: https://github.com/facebookresearch/many-to-many-dijkstra Note: current model accuracy is approximately 70% when compared to existing ground-truthed data. Accuracy can be further improved by integrating other locally-relevant information into the model and running it again. Resolution: geotiff is provided at Bing Tile Level 20

Social network X/Twitter is particularly popular in the United States, and as of February 2025, the microblogging service had an audience reach of 103.9 million users in the country. Japan and the India were ranked second and third with more than 70 million and 25 million users respectively. Global Twitter usage As of the second quarter of 2021, X/Twitter had 206 million monetizable daily active users worldwide. The most-followed Twitter accounts include figures such as Elon Musk, Justin Bieber and former U.S. president Barack Obama. X/Twitter and politics X/Twitter has become an increasingly relevant tool in domestic and international politics. The platform has become a way to promote policies and interact with citizens and other officials, and most world leaders and foreign ministries have an official Twitter account. Former U.S. president Donald Trump used to be a prolific Twitter user before the platform permanently suspended his account in January 2021. During an August 2018 survey, 61 percent of respondents stated that Trump's use of Twitter as President of the United States was inappropriate.

This tile layer presents a vector basemap of OpenStreetMap (OSM) data hosted by Esri. Esri created this vector tile basemap from the Daylight map distribution of OSM data, which is supported by Facebook and supplemented with additional data from Microsoft. This version of the map is rendered in a style similar to the Esri Street Map (with Relief). It is designed for use with world hillshade. The GCS vector tiles are updated quarterly.OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this new vector basemap available available to the OSM, GIS, and Developer communities.Precise Tile Registration: The tile layer uses the improved tiling scheme “WGS84 Geographic, Version 2” to ensure proper tile positioning at higher resolutions (neighborhood level and beyond). The new tiling scheme is much more precise than tiling schemes of the legacy basemaps Esri released years ago. We recommend that you start using this new basemap for any new web maps in WGS84 that you plan to author. Due to the number of differences between the old and new tiling schemes, some web clients will not be able to overlay tile layers in the old and new tiling schemes in one web map.