The main goal of the DFS data collection project is to map the online friendship networks of Dutch adolescents. Specifically, the Facebook networks of Dutch adolescents participating in the offline CILS4EU and CILSNL data collection are mapped. Facebook is an American social networking site (SNS) where users create an online profile, provide personal information on this profile and invite other users to become connected as friends. With these connections, users can interact via personal messaging, post directly on others’ personal profile pages and react to others’ posts. During the time of our data collection, in 2014, Facebook was the largest SNS of the world with approximately 1.3 billion members. The DFS data are collected to study the relationship between offline face-to-face contacts, and online friendship network on Facebook. To this purpose we coded variables that show respondents’ Facebook friends’ gender, numbers of friends, privacy settings and ethnicity.
The global number of Facebook users was forecast to continuously increase between 2023 and 2027 by in total *** million users (+***** percent). After the fourth consecutive increasing year, the Facebook user base is estimated to reach *** 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).
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The files of this dataset are no longer available. A revised version has been published at: https://doi.org/10.17026/dans-235-tba9The main goal of the DFS data collection project is to map the online friendship networks of Dutch adolescents. Specifically, the Facebook networks of Dutch adolescents participating in the offline CILS4EU and CILSNL data collection are mapped. Facebook is an American social networking site (SNS) where users create an online profile, provide personal information on this profile and invite other users to become connected as friends. With these connections, users can interact via personal messaging, post directly on others’ personal profile pages and react to others’ posts. During the time of our data collection, in 2014, Facebook was the largest SNS of the world with approximately 1.3 billion members. The DFS data are collected to study the relationship between offline face-to-face contacts, and online friendship network on Facebook. To this purpose we coded variables that show respondents’ Facebook friends’ gender, numbers of friends, privacy settings and ethnicity.
Supermarkets are one of the most popular and convenient ways in which Americans gain access to healthy food, such as fresh meat and fish, or fresh fruits and vegetables. There are various ways in which people gain access to supermarkets. People in the suburbs drive to supermarkets and load up the car with many bags of food. People in cities depend much more on walking to the local store, or taking a bus or train.This map came about after asking a simple question: how many Americans live within a reasonable walk or drive to a supermarket?In this case, "reasonable" was defined as a 10 minute drive, or a 1 mile walk. The ArcGIS Network Analyst extension performed the calculations on streets data from StreetMap Premium, and the ArcGIS Spatial Analyst extension created a heat map of the walkable access and drivable access to supermarkets.The green dots represent populations in poverty who live within one mile of a supermarket. The red dots represent populations in poverty who live beyond a one mile walk to a supermarket, but may live within a 10 minute drive...which presumes they have access to a car or public transit. The grey dots represent the total population in a given area.This is an excellent map to use as backdrop to show how people are improving access to healthy food in their community. Open this map in ArcGIS Pro or ArcGIS Online to use it as a backdrop to your local analysis work. Or open it in ArcGIS Explorer to add your favorite farmers' market, CSA, or transit line -- then share that map via Facebook, Twitter or email.This map shows data for the entire U.S. The supermarkets included in the analysis have annual sales of $1 million or more.Data source: see this map package.
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.
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Summary of the Twitter and Facebook data collected.
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
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Tweets and Facebook posts per project obtained–Strategy 1.
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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.
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Examples of tweets and Facebook posts with quantitative evidence of social impact.
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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.
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The High Resolution Settlement Layer (HRSL) provides estimates of human population distribution at a resolution of 1 arc-second (approximately 30m) for the year 2015. The population estimates are based on recent census data and high-resolution (0.5m) satellite imagery from DigitalGlobe. The population grids provide detailed delineation of settlements in both urban and rural areas, which is useful for many research areas—from disaster response and humanitarian planning to the development of communications infrastructure. The settlement extent data were developed by the Connectivity Lab at Facebook using computer vision techniques to classify blocks of optical satellite data as settled (containing buildings) or not. Center for International Earth Science Information Networks (CIESIN) at Earth Institute Columbia University used proportional allocation to distribute population data from subnational census data to the settlement extents.
The data-sets contain the population surfaces, metadata, and data quality layers. The population data surfaces are stored as GeoTIFF files for use in remote sensing or geographic information system (GIS) software.
The data can also be explored via an interactive map - http://columbia.maps.arcgis.com/apps/View/index.html?appid=ce441db6aa54494cbc6c6cee11b95917
Citation: Facebook Connectivity Lab and Center for International Earth Science Information Network - CIESIN - Columbia University. 2016. High Resolution Settlement Layer (HRSL). Source imagery for HRSL © 2016 DigitalGlobe.
To gain a deeper understanding of the perspectives, challenges, and opportunities for small and medium sized businesses (SMBs) around the world during the COVID-19 pandemic, Facebook and partners collaborate to collect and share timely information with the broader community. The State of Small Business (SoSB) Survey surveys SMBs, employees, and consumers from approximately 30 countries across the globe. This combination of survey respondents allows us to evaluate how the impacts on SMBs, their employees, and their clients have developed throughout 2021.
Argentina Australia Belgium Brazil Canada Colombia Egypt France Germany Ghana India Indonesia Ireland Israel Italy Kenya Mexico Nigeria Pakistan Philippines Poland Portugal Russian Federation (the) South Africa Spain Taiwan Turkey United Kingdom of Great Britain and Northern Ireland United States of America (the) Vietnam
The study describes small and medium-sized business owners, their employees and consumers.
The survey uses a random sample of SMB leaders with Facebook Page administrator privileges and of the general population of Facebook users. Therefore, the sample covered in the survey is representative of SMB leaders surveyable through Facebook at the country level.
Sample survey data [ssd]
The survey reaches a random sample of SMB leaders with Facebook Page administrator privileges and of the general population of Facebook users. A random sample of firms, representing the target population in each country, is selected to respond to the survey. To achieve better representation of the broader small business population on Facebook, Facebook also weights our results based on known characteristics of the Facebook Page admin population.
Internet [int]
Questions cover a range of topics depending on the survey wave such as business characteristics, challenges, financials and strategy in addition to custom modules related to regulation, access to finance, digital technologies, reduction in revenues, business closures, reduction of employees and challenges/needs of the business
Response rates to online surveys vary widely depending on a number of factors including survey length, region, strength of the relationship with invitees, incentive mechanisms, invite copy, interest of respondents in the topic and survey design. To achieve better representation of the broader small business population on Facebook, Facebookwe also weights our results based on known characteristics of the Facebook Page admin population.
Note: Response rates are calculated as the number of respondents who completed the survey divided by the total number of SMBs invited.
Any survey data is prone to several forms of error and biases that need to be considered to understand how closely the results reflect the intended population. In particular, the following components of the total survey error are noteworthy: Sampling error is a natural characteristic of every survey based on samples and reflects the uncertainty in any survey result that is attributable to the fact that not the whole population is surveyed.Other factors beyond sampling error that contribute to such potential differences are frame or coverage error (sampling frame of Page owners does not include all relevant businesses but also may include individuals that don’t represent businesses), and nonresponse error.
Note that the sample is meant to reflect the population of businesses on Facebook, not the population of small businesses in general. This group of digitized SMEs is itself a community worthy of deeper consideration and of considerable policy interest. However, care should be taken when extrapolating to the population of SMEs in general. Moreover, future work should evaluate the external validity of the sample. Particularly, respondents should be compared to the broader population of SMEs on Facebook, and the economy as a whole.
Facebook’s Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. This survey covers topics about gender dynamics and norms, unpaid caregiving, and life during the COVID-19 pandemic. Aggregated data is available publicly on Humanitarian Data Exchange (HDX). De-identified microdata is also available to eligible nonprofits and universities through Facebook’s Data for Good (DFG) program. For more information, please email dataforgood@fb.com.
This survey is fielded once a year in over 200 countries and 60 languages. The data can help researchers track trends in gender equality and progress on the Sustainable Development Goals.
The survey was fielded to active Facebook users.
Sample survey data [ssd]
Respondents were sampled across seven regions: - East Asia and Pacific; Europe and Central Asia - Latin America and Caribbean - Middle East and North Africa - North America - Sub-Saharan Africa - South Asia
For the purposes of this report, responses have been aggregated up to the regional level; these regional estimates form the basis of this report and its associated products (Regional Briefs). In order to ensure respondent confidentiality, these estimates are based on responses where a sufficient number of people responded to each question and thus where confidentiality can be assured. This results in a sample of 461,748 respondents.
The sampling frame for this survey is the global database of Facebook users who were active on the platform at least once over the past 28 days, which offers a number of advantages: It allows for the design, implementation, and launch of a survey in a timely manner. Large sample sizes allow for more questions to be asked through random assignment of modules, avoiding respondent fatigue. Samples may be drawn from diverse segments of the online population. Knowledge of the overall sampling frame allowed for more rigorous probabilistic sampling techniques and non-response adjustments than is typical for online and phone surveys
Internet [int]
The survey includes a total of 75 questions, split across into the following sections: - Basic demographics and gender norms - Decision making and resource allocation across household members - Unpaid caregiving - Additional household demographics and COVID-19 impact - Optional questions for special groups (e.g. students, business owners, the employed, and the unemployed)
Questions were developed collaboratively by a team of economists and gender experts from the World Bank, UN Women, Equal Measures 2030, and Ladysmith. Some of the questions have been borrowed from other surveys that employ alternative modes of administration (e.g., face-to-face, telephone surveys, etc.); this allows for comparability and identification of potential gaps and biases inherent to Facebook and other online survey platforms. As such, the survey also generates methodological insights that are useful to researchers undertaking alternative modes of data collection during the COVID-19 era.
In order to avoid “survey fatigue,” wherein respondents begin to disengage from the survey content and responses become less reliable, each respondent was only asked to answer a subset of questions. Specifically, each respondent saw a maximum of 30 questions, comprising demographics (asked of all respondents) and a set of additional questions randomly and purposely allocated to them.
Response rates to online surveys vary widely depending on a number of factors including survey length, region, strength of the relationship with invitees, incentive mechanisms, invite copy, interest of respondents in the topic and survey design.
Any survey data is prone to several forms of error and biases that need to be considered to understand how closely the results reflect the intended population. In particular, the following components of the total survey error are noteworthy:
Sampling error is a natural characteristic of every survey based on samples and reflects the uncertainty in any survey result that is attributable to the fact that not the whole population is surveyed.
Other factors beyond sampling error that contribute to such potential differences are frame or coverage error and nonresponse error.
Survey Limitations The survey only captures respondents who: (1) have access to the Internet (2) are Facebook users (3) opt to take this survey through the Facebook platform. Knowledge of the overall demographics of the online population in each region allows for calibration such that estimates are representative at this level. However, this means the results only tell us something about the online population in each region, not the overall population. As such, the survey cannot generate global estimates or meaningful comparisons across countries and regions, given the heterogeneity in internet connectivity across countries. Estimates have only been generated for respondents who gave their gender as male or female. The survey included an “other” option but very few respondents selected it, making it impossible to generate meaningful estimates for non-binary populations. It is important to note that the survey was not designed to paint a comprehensive picture of household dynamics but rather to shed light on respondents’ reported experiences and roles within households
Supermarkets are one of the most popular and convenient ways in which Americans gain access to healthy food, such as fresh meat and fish, or fresh fruits and vegetables. There are various ways in which people gain access to supermarkets. People in the suburbs drive to supermarkets and load up the car with many bags of food. People in cities depend much more on walking to the local store, or taking a bus or train.This map came about after asking a simple question: how many Americans live within a reasonable walk or drive to a supermarket?In this case, "reasonable" was defined as a 10 minute drive, or a 1 mile walk. The ArcGIS Network Analyst extension performed the calculations on streets data from StreetMap Premium, and the ArcGIS Spatial Analyst extension created a heat map of the walkable access and drivable access to supermarkets.The green dots represent populations in poverty who live within one mile of a supermarket. The red dots represent populations in poverty who live beyond a one mile walk to a supermarket, but may live within a 10 minute drive...which presumes they have access to a car or public transit. The grey dots represent the total population in a given area.This is an excellent map to use as backdrop to show how people are improving access to healthy food in their community. Open this map in ArcGIS Pro or ArcGIS Online to use it as a backdrop to your local analysis work. Or open it in ArcGIS Explorer to add your favorite farmers' market, CSA, or transit line -- then share that map via Facebook, Twitter or email. See this web map for a map with a popup layer.This map shows data for the entire U.S. The supermarkets included in the analysis have annual sales of $1 million or more.Data source: see this map package.
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Timeframe for the extraction of Twitter and Facebook data.
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“The service that was providing camera images has been decommissioned and therefore this dataset that had links to the images has been retired and will no longer be available for public access.The …Show full description“The service that was providing camera images has been decommissioned and therefore this dataset that had links to the images has been retired and will no longer be available for public access.The current webcams that were providing this service are reaching the end of life and are no longer fit for purpose. As a consequence they are becoming unreliable, unstable and the level of service is deteriorating. We appreciate your use of the service to date and apologise for any inconvenience this may cause you. Depending upon your need you can obtain information on the entire State road network via the Travel Map available from our website, via our Twitter accounts or for metropolitan road information via our Perth Traffic Facebook group.”Fixed traffic cameras have been installed across the state road network, providing the general public with vision of traffic hotspots to assist with journey planning.Note that you are accessing this data pursuant to a Creative Commons (Attribution) Licence which has a disclaimer of warranties and limitation of liability. You accept that the data provided pursuant to the Licence is subject to changes.Pursuant to section 3 of the Licence you are provided with the following notice to be included when you Share the Licenced Material:- The Commissioner of Main Roads is the creator and owner of the data and Licenced Material, which is accessed pursuant to a Creative Commons (Attribution) Licence, which has a disclaimer of warranties and limitation of liability.Creative Commons CC BY 4.0 https://creativecommons.org/licenses/by/4.0/
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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
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Village (Neighborhood) Boundaries across the Nation
The main goal of the DFS data collection project is to map the online friendship networks of Dutch adolescents. Specifically, the Facebook networks of Dutch adolescents participating in the offline CILS4EU and CILSNL data collection are mapped. Facebook is an American social networking site (SNS) where users create an online profile, provide personal information on this profile and invite other users to become connected as friends. With these connections, users can interact via personal messaging, post directly on others’ personal profile pages and react to others’ posts. During the time of our data collection, in 2014, Facebook was the largest SNS of the world with approximately 1.3 billion members. The DFS data are collected to study the relationship between offline face-to-face contacts, and online friendship network on Facebook. To this purpose we coded variables that show respondents’ Facebook friends’ gender, numbers of friends, privacy settings and ethnicity.