Facebook received 73,390 user data requests from federal agencies and courts in the United States during the second half of 2023. The social network produced some user data in 88.84 percent of requests from U.S. federal authorities. The United States accounts for the largest share of Facebook user data requests worldwide.

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.

As of April 2024, Facebook had an addressable ad audience reach 131.1 percent in Libya, followed by the United Arab Emirates with 120.5 percent and Mongolia with 116 percent. Additionally, the Philippines and Qatar had addressable ad audiences of 114.5 percent and 111.7 percent.

Seamless Interaction Dataset

A large-scale multimodal dataset of 4,000+ hours of human interactions for AI research

🖼️ Blog

🌐 Website

🎮 Demo

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📄 Paper

Human communication involves a complex interplay of verbal and nonverbal signals, essential for conveying meaning and achieving interpersonal goals. The Seamless Interaction Dataset is a large-scale collection of over 4,000 hours of face-to-face interaction footage from more than 4,000 participants in… See the full description on the dataset page: https://huggingface.co/datasets/facebook/seamless-interaction.

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.

Purpose For the purpose of informing tobacco intervention programs, this dataset was created and used to explore how online social networks of smokers differed from those of nonsmokers. The study was a secondary analysis of data collected as part of a randomized control trial conducted within Facebook. (See "Other References" in "Metadata" for parent study information.) Basic description of 4 anonymized data files of study participants. fbr_friends: Anonymized Facebook friends networks, basic ego demographics, basic ego social media activity fbr_family: Anonymized Facebook family networks, basic ego demographics, basic ego social media activity fbr_photos: Anonymized Facebook photo networks, basic ego demographics, basic ego social media activity fbr_groups: Anonymized Facebook group networks, basic ego demographics, basic ego social media activity Each network comprises the ego, the ego's first degree connections, and the (second degree) connections between the ego's friends. Missing data and users who did not have friend, family, photo, or group networks were cleaned from the data beforehand. Each data file contains the following columns of data, taken with participant knowledge and consent participant_id: Nonidentifying ids assigned to different study participants. is_smoker: Binary value (0,1) that takes on the value 1 if participant was a smoker and 0 otherwise. gender: One of three categories: male, female, or blank, which signified Other (different from missing data). country: One of four categories: Canada (ca), US (us), Mexico (mx), or Other (xx). likes_count: Numeric data indicating number of Facebook likes the participant had made up to the date the data was collected. wall_count: Numeric data indicating number of Facebook wall posts the participant had made up to the date the data was collected. t_count_page_views: Numeric data indicating number of pages participant had visited in the UbiQUITous app up to the date the data was collected. yearsOld: Numeric data indicating age in years of the participant; right censored at 90 years for data anonymity. vertices: Number of people in the participant's network. edges: Number of connections between people in the network. density: The portion of potential connections in a network that are actual connections; a network-level metric; calculated after removing ego and isolates. mean_betweenness_centrality: An average of the relative importance of all individuals within their own network; a network-level metric; calculated after removing ego and isolates. transitivity: The extent to which the relationship between two nodes in a network that are connected by an edge is transitive (calculated as the number of triads divided by all possible connections); a network-level metric; calculated after removing ego and isolates. mean_closeness: Average of how closely associated members are to one another; a network-level metric; calculated after removing ego and isolates. isolates2: Number of individuals with no connections other than to the ego; a network-level metric. diameter3: Maximum degree of separation between any two individuals in the network; a network-level metric; calculated after removing ego and isolates. clusters3: Number of subnetworks; a network-level metric; calculated after removing ego and isolates. communities3: Number of groups, sorted to increase dense connections within the group and decrease sparse connections outside it (i.e., to maximize modularity); a network-level metric; calculated after removing ego and isolates. modularity3: The strength of division of a network into communities (calculated as the fraction of ties between community members in excess of the expected number of ties within communities if ties were random); a network-level metric. Detailed information on network metrics in the associated manuscript: "An exploration of the Facebook social networks of smokers and non-smokers" by Fu, L, Jacobs MA, Brookover J, Valente TW, Cobb NK, and Graham AL.

Dataset Card for PLM-Video Human

PLM-Video-Human is a collection of human-annotated resources for training Vision Language Models, focused on detailed video understanding. Training tasks include: fine-grained open-ended question answering (FGQA), Region-based Video Captioning (RCap), Region-based Dense Video Captioning (RDCap) and Region-based Temporal Localization (RTLoc). [📃 Tech Report] [📂 Github]

  Dataset Structure






  Fine-Grained Question Answering… See the full description on the dataset page: https://huggingface.co/datasets/facebook/PLM-Video-Human.

As of April 2024, it was found that men between the ages of 25 and 34 years made up Facebook largest audience, accounting for 18.4 percent of global users. Additionally, Facebook's second largest audience base could be found with men aged 18 to 24 years.

              Facebook connects the world

              Founded in 2004 and going public in 2012, Facebook is one of the biggest internet companies in the world with influence that goes beyond social media. It is widely considered as one of the Big Four tech companies, along with Google, Apple, and Amazon (all together known under the acronym GAFA). Facebook is the most popular social network worldwide and the company also owns three other billion-user properties: mobile messaging apps WhatsApp and Facebook Messenger,
              as well as photo-sharing app Instagram. Facebook usersThe vast majority of Facebook users connect to the social network via mobile devices. This is unsurprising, as Facebook has many users in mobile-first online markets. Currently, India ranks first in terms of Facebook audience size with 378 million users. The United States, Brazil, and Indonesia also all have more than 100 million Facebook users each.

Information containing physical address of the Office of Inspector General, Department of Commerce locations. The site also contains links to the OIG hotline, Commerce People Finder, Twitter Account, Facebook page, OIG Webmaster, and OIG FOIA page,

Calculation of the percentage of elderly people in relation to the total population of each municipality using data extracted from Facebook. Data have been transformed by GIS4Tech.

For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.

What is Amazon?

Amazon.com, Inc. is an American multinational technology company which focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence. It is one of the Big Five companies in the U.S. information technology industry, along with Google, Apple, Microsoft, and Facebook. The company has been referred to as "one of the most influential economic and cultural forces in the world", as well as the world's most valuable brand.

Data Description

This dataset provides the history of daily prices of Amazon stock (AMZN). All the column descriptions are provided. Currency is USD.

Researchers at New York University, the University of Texas at Austin, and other academic institutions, as well as Meta, partnered with NORC at the University of Chicago to understand more about how the information people see on Facebook and Instagram affects their opinions and behaviors. This dataset contains survey, web browsing, voter turnout, and campaign contribution data associated with the U.S. 2020 Facebook and Instagram Election Study. Read more about the project here.

This dataset is gleaned from employing a netnography methodology whereby Facebook posts and media content from London Latin American focused Facebook groups from 2021 backwards were extracted and analysed using Nvivo software. The posts were searched for their relevance to the Elephant and Castle mall in London, a hub from the Latin American community, and the effect of the closing of the hub on the wellbeing of the residences who posted about it. The study was to uncover wellbeing issues that effected displaced populations. The posts and videos were assessed and keywords systematically picked out for snowball analysis, regularity and presence within certain groups. This aided the identification of those factors most relevant to the wellbeing of these migrant groups. The dataset breaks down the number of mentions in individual posts (rather than the total mentions, where some posts may mention the same wellbeing factor more than once). It separates the wellbeing factors (lefthand column) against national groupings identified by the name of the individual Facebook group where the content of those posts originated.This research directly addresses the 'Sustainability, equity, wellbeing and cultural connections' aspects identified in the call. It investigates through what processes forcibly displaced people become part of cities, in ways that sustainably contribute to economic development, cultural advancement and wellbeing. To this end, we will build a detailed understanding of the relations between placemaking processes, modalities of reception and wellbeing outcomes for displaced groups in Indian and European cities. We do this in a context of rapidly growing human displacement, forced migration and refugee flows to cities globally, and in European and Indian cities that are witnessing rising inequalities. The research objectives, in approximate order of importance, are: (i) Gain a deep understanding of the material and cultural production, design and architectural organisation of urban spaces of displacement and placemaking processes. (ii) Critically examine the ways in which these spaces and the displaced people in them are governed, through assemblages of actors and particular modalities of reception, to produce particular wellbeing effects. (iii) Assess in what ways and why displaced people negotiate access to these spaces. (iv) Develop, design and build strategic interventions that foster equity and inclusion in urban spaces, grounded in the wellbeing priorities of vulnerable displaced groups. (v) Build student and academic capacity for current and future cross- and trans-disciplinary research, design and learning relating to migration management in cities. To achieve these objectives, the study is guided by an overarching research question: How to curate processes that foster displaced people to become part of the city, and to sustainably contribute to its economic development, socio-cultural cohesion and wellbeing? This question is broken down into four sub-questions: 1. Through what kinds of placemaking processes in physical and digital spaces do displaced people inhabit, build, make, give meaning and derive wellbeing? 2. In what ways and why do modalities of reception structure economic participation, socio-cultural cohesion and wellbeing outcomes for displaced people? 3. What is the role of urban informality, temporality and scale in placemaking processes and in the visions and functioning of modalities of reception? 4. What strategic architectural and policy interventions can advance equity and wellbeing for displaced communities in urban spaces? These questions, along with the wellbeing framework and the highly interdisciplinary methods that the study proposes, ensure that it addresses cross-cutting issues and themes highlighted by the study call, including urban inequalities, the (formal and informal) urban governance features, and practices that interact with vulnerable groups as they are engaged in placemaking processes to critically shape equity and wellbeing outcomes. The project will convene European and Indian social science and humanities research communities to jointly conduct cross-country investigations into urban protracted displacement across lower-middle income (India) and higher income countries (Finland, Norway, UK). The comparative case study analysis across cities of various scales (from town to megacity) will advance new empirical, conceptual and theoretical insights. This project also offers a unique approach to analysis and capacity building, making sure that the insights and skills gained amongst the consortium will last beyond the end of the project. We will systematically pair senior researchers and students from Architecture and Design studies and Social Sciences to advance a highly inter-disciplinary approach that has great potential to generate new insights and to advance architectural and policy solutions that address growing urban inequalities and economic development, and improve equity and socio-cultural wellbeing in a sustainable manner. This netnography was conducted using simple tools and can be easily replicated. A Facebook search for groups consisting of Latin migrants in London was performed with the ‘groups’ filter selected and city set to ‘London’. Two sets of keyword searches were carried out. The first included the words ‘Latin’, ‘Latino’, ‘Latina’, ‘Latinx’ combined with ‘London’, ‘Londres’ (Spanish), ‘Southwark’, or ‘Elephant’. The second set consisted of the English and Spanish variation of 20 Spanish speaking Latin American nationalities (e.g. Argentineans and Argentinos) combined with ‘London’ or ‘Londres’. 89 Groups were uncovered of which 51 public groups were analysed. Private groups were NOT analysed. Groups consisting of both Latino and Spaniards in London were not included. NViVo’s nCapture feature allows users to scrape data from Facebook group pages and export it into a spreadsheet. However, spreadsheet are only generated for posts loaded on a browser and only a few posts are visible when group pages are opened (approx. 10). Many of the pages analysed included thousands of posts making scrolling through pages inefficient. Instead, relevant posts were uncovered using Facebook’s Search button within each Facebook group located at the top right of each Group page (see photo below). The first search was for ‘Elephant’. This automatically returned misspelled variations of ‘Elephant’ like ‘Elefan’. This search returned posts mentioning E&C and posts where E&C was mentioned in a Post’s comments section. Searches were done for the Spanish words for ‘where’ (Donde) and ‘Does anyone know’ (Alguien Sabe). This returned further posts where users were referred to E&C in the comments and results where E&C was not recommended. Results and Individual posts were scraped using nCapture which converted the page into a PDF-like file. 350 individual posts were uploaded to NVivo where they were qualitatively coded and analyzed. Codes were derived through a brainstorming exercise after reviewing a set of 50 posts and tweaked to fit the paper’s theoretical framework. Unanticipated themes arising during the coding process were also added. Limitations It is unlikely all comments mentioning E&C were captured using this approach. Facebook does not make it clear under what conditions search results return comment mentions. Thus, this study can only claim to be illustrative rather than exhaustive.

This survey charted the gambling, social media usage and subjective well-being of young people aged 15-25 years in the United States. The study was conducted as part of the "Problem Gambling and Social Media: Social Psychological Study on Youth Behaviour in Online Gaming Communities" research project. The aim of the project was to analyse how young social media users evaluate, adopt and share gambling-related online content and how online group processes affect their gambling and gambling-related attitudes. FSD's holdings also include two other datasets that were collected using a nearly identical questionnaire (FSD3399 and FSD3400). Data for the research project have been collected in Finland, the United States, Spain, and South Korea. First, the respondents were asked which social media services they used (e.g. Facebook, YouTube, Instagram, discussion forums, online casinos) and how often. Topics that the respondents discussed on gambling-related social media were charted more closely, and they were asked, for example, whether the discussion usually related to instructions or tips on gambling or to problem gambling and recovering from problem gambling. Some questions on the respondents' social media activity were also presented, for instance, how often they saw gambling-related advertising online, how often they changed their most important social media passwords, and how often they uploaded pictures of themselves on social media. The respondents were asked whether they had ever been harassed online or had been the victim of a crime on the Internet in the past three years (e.g. defamation, identity theft, fraud, sexual harassment). The respondents' identity bubbles on social media were surveyed by using the IBR scale (Identity Bubble Reinforcement Scale). The respondents were asked, for instance, whether they thought they could be themselves on social media and whether they only interacted with people similar to them on social media. Additionally, the CIUS scale (Compulsive Internet Use) was used to examine problems related to Internet use. Questions focused on, for example, whether the respondents found it difficult to stop using the Internet when they were online, whether people close to them said they should use the Internet less, and whether they felt restless, frustrated or irritated when they couldn't use the Internet. In the next section of the questionnaire, the respondents were randomly assigned to two groups for a vignette experiment. Respondents in the test group were told they belong to Group C because they had answered the earlier questions in a similar manner to others in the group. Those in the control group were given no information on the group. The respondents were presented with different gambling-related social media scenarios, and they were asked to evaluate the contents of the gambling-related messages by "liking" or "disliking" the message or by not reacting to it at all. Each respondent was shown four different gambling messages with different contents. Three factors were manipulated in the scenarios (2x2x2 design): expressed stance of the message on gambling (positive or negative), narrative perspective of the message (experience-driven first-person narration or fact-driven third-person narration) and majority opinion of other respondents on the message (positively or negatively biased distribution of likes or dislikes). For Group C, the majority opinion was seemingly provided by other Group C members, whereas for the control group the majority opinion was seemingly provided by other respondents. Additionally, the respondents' attitudes towards the message were surveyed with statements regarding, for instance, how likely they would find the message interesting or share it on social media. Next, the respondents' attitudes towards gambling were charted by using the ATGS scale (Attitudes Towards Gambling Scale). They were asked, for example, whether people should have the right to gamble whenever they want, whether most people who gamble do so sensibly and whether it would be better if gambling was banned altogether. The respondents' gambling habits were examined by using the SOGS scale (South Oaks Gambling Screen), and they were asked, for instance, which types of gambling they had done in the past 12 months (played slot machines, visited an online casino, bet on lotteries etc.), whether the people close to them had gambling problems, and whether they had borrowed money to gamble or to pay gambling debts. In addition, the respondents' alcohol consumption was surveyed with a few questions from the AUDITC scale (The Alcohol Use Disorders Identification Test), and they were asked whether they had used various drugs for recreational purposes (e.g. cannabis, LSD, amphetamine, opioids) and which online resources they had used to purchases these drugs (e.g. Facebook, Instagram, Craigslist). The respondents' subjective well-being and social relationships were examined next. The respondents were asked how happy they were in general and how satisfied they were with their economic situation and life in general. They were also asked how well the single statement "I have high self-esteem" from the SISE scale (Single-item Self-esteem Scale) described them. The three statements on lacking companionship, feeling left out and feeling isolated from the LONE scale (Three-item Loneliness Scale) were also included in the survey. Feelings of belonging to different groups or communities (e.g. family, friends, neighbourhood, parish/religious community) were charted, and the 12-item GHQ scale (General Health Questionnaire) was used to survey the respondents' recent mental health. Questions included, for example, whether the respondents had been able to concentrate on what they were doing, had felt they couldn't overcome their difficulties, and had been losing confidence in themselves. Finally, the respondents' sense of control over the events in their lives was examined with the MASTERY scale (Sense of Mastery Scale), with questions focusing on, for instance, whether they thought they had little control over the things that happen to them and whether they often felt helpless in dealing with the problems of life. The respondents' impulsivity was surveyed by using the EIS scale (Eysenck Impulsivity Scale) and their willingness to delay gratification was surveyed with the GRATIF scale (Delay of Gratification). Background variables included the respondent's gender, age, country of birth (own and parents') level of education, type of municipality of residence, household composition, disposable income, possible financial problems, and economic activity and occupational status.

AlekseyKorshuk/persona-chat dataset hosted on Hugging Face and contributed by the HF Datasets community

What is the City doing? The City is developing a planning vision to bring together opportunities in the City’s key areas of focus and position Brampton as a future city and a hub for jobs and innovation. In other words, it aims to set Brampton apart from other suburban cities as a model city that people are proud to call home. The work focuses on understanding what Brampton can – and will be – in 25+ years, and how to get there.Why should it matter to me?Brampton has the right ingredients to be a future ready city. From a diverse, rapidly growing population, to a key position on the innovation super-corridor, we’ve got a lot going for us. We’re thinking bigger about our brilliant future – but to really be successful, we need your bright ideas. This is your city, and it’s important for us to know what its future looks like to you. You can always email us at brightideas@brampton.ca, or send us messages on Twitter or Facebook with any questions or comments you have. For data captured through the Bang the Table™ Web Site, visit the following.Terms and Conditions | Privacy Policy I keep hearing the term “future ready”, what does that mean?Moving Brampton forward to be a “future ready” city means thinking bigger about opportunities that fuel its vibrancy. It means thinking bigger about what Brampton will look like in 5, 10 and 25 years and beyond. Community input is critical – which is why we need you!

During a 2024 survey among marketers worldwide, around 86 percent reported using Facebook for marketing purposes. Instagram and LinkedIn followed, respectively mentioned by 79 and 65 percent of the respondents.

              The global social media marketing segment

              According to the same study, 59 percent of responding marketers intended to increase their organic use of YouTube for marketing purposes throughout that year. LinkedIn and Instagram followed with similar shares, rounding up the top three social media platforms attracting a planned growth in organic use among global marketers in 2024. Their main driver is increasing brand exposure and traffic, which led the ranking of benefits of social media marketing worldwide.

              Social media for B2B marketing

              Social media platform adoption rates among business-to-consumer (B2C) and business-to-business (B2B) marketers vary according to each subsegment's focus. While B2C professionals prioritize Facebook and Instagram – both run by Meta, Inc. – due to their popularity among online audiences, B2B marketers concentrate their endeavors on Microsoft-owned LinkedIn due to its goal to connect people and companies in a corporate context.

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

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

              How popular is Instagram?

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

              Who uses Instagram?

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

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

During a January 2024 global survey among marketers, nearly 60 percent reported plans to increase their organic use of YouTube for marketing purposes in the following 12 months. LinkedIn and Instagram followed, respectively mentioned by 57 and 56 percent of the respondents intending to use them more. According to the same survey, Facebook was the most important social media platform for marketers worldwide.