As of February 2025, it was found that men between the ages of 25 and 34 years made up Facebook's largest audience, accounting for 18.5 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.

1) Data Introduction • The Facebook Data is a social network analysis data that can be used to identify key user groups that can contribute to business growth and develop recommendation strategies, including Facebook users' activity patterns, interactions, likes, friendships, gender, and age.

2) Data Utilization (1) Facebook Data has characteristics that: • This dataset consists of numerical and categorical variables such as user ID, gender, age, number of friends, number of likes (mobile/web), number of friend requests, number of likes received/sent, and frequency of activities, allowing you to analyze user-specific behavioral characteristics and interaction patterns from multiple angles. (2) Facebook Data can be used to: • Core User Group Targeting and Recommendation Strategies: Use key characteristics such as gender, age, frequency of activity, friends and likes to identify user groups that have a significant impact on business growth and to develop customized content and advertising recommendation strategies. • Analysis of Usage Behavior and Platform Trends: Mobile and Web-based Good By analyzing data such as distribution, age and gender activity patterns, and friend relationship formation, you can visually explore changes in user usage behavior and major trends within the platform.

This statistical dataset contains estimates on the number of active online Facebook users living outside of their country of origin within the European Union. The dataset includes information on Facebook users' age, gender, country of residence, and country of previous residence. The data is divided in the number of Monthly Active Users and Daily Active Users. The data was collected through standard CSV format via an advertising API platform by using an R Studio code, and the data collection was conducted twice a month from January to November 2021.

The dataset was originally published in DiVA and moved to SND in 2024.

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.

The LiLaH-HAG dataset (HAG is short for hate-age-gender) consists of metadata on Facebook comments to Facebook posts of mainstream media in Great Britain, Flanders, Slovenia and Croatia. The metadata available in the dataset are the hatefulness of the comment (0 is acceptable, 1 is hateful), age of the commenter (0-25, 26-30, 36-65, 65-), gender of the commenter (M or F), and the language in which the comment was written (EN, NL, SL, HR).

The hatefulness of the comment was assigned by multiple well-trained annotators by reading comments in the order of appearance in a discussion thread, while the age and gender variables were estimated from the Facebook profile of a specific user by a single annotator.

According to a global survey conducted in February 2024, almost 40 percent of Facebook users paid attention to news from mainstram news outlets and mainstream journalists on the social network. Additionally, 39 percent reported paying attention to personalities, such as celebrities and influencers. Around one in four Facebook users paid attention to politicians and politican activists on the network.

Survey data collected in Canada, 2019. n = 1539. Using, Age, Facebook use and meme understanding to determine differences between demographics in relation to Instagram use

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

Context Collection of Facebook spam-legit profile and content-based data. It can be used for classification tasks.

Content The dataset can be used for building machine learning models. To collect the dataset, Facebook API and Facebook Graph API are used and the data is collected from public profiles. There are 500 legit profiles and 100 spam profiles. The list of features is as follows with Label (0-legit, 1-spam). 1. Number of friends 2. Number of followings 3. Number of Community 4. The age of the user account (in days) 5. Total number of posts shared 6. Total number of URLs shared 7. Total number of photos/videos shared 8. Fraction of the posts containing URLs 9. Fraction of the posts containing photos/videos 10. Average number of comments per post 11. Average number of likes per post 12. Average number of tags in a post (Rate of tagging) 13. Average number of hashtags present in a post

Inspiration Dataset helps the community to understand how features can help to differ Facebook legit users from spam users.

This dataset was utilized in the analyses presented in the paper entitled "Information Bubble and Learning in the Digital Age: An Analysis from the Perspective of European and African Students." Details regarding the dataset can be found in the Methodology section of the paper.

This dataset contains detailed Facebook advertising data for the political party Sumar and its leader Yolanda Díaz for the period from 9 January to 21 July 2023. This timeframe includes the campaign and pre-campaign periods of the 2023 Spanish general election. The dataset provides a comprehensive overview of the party's advertising strategies on Facebook, including unique ad IDs from Facebook's ad library, average cost per ad, dates, ad text, links, ad categories and estimated reach segmented by age, gender and geography. The dataset also includes information on the languages used in the ads, providing insights into the party's targeting and communication approaches during this crucial election period.

Context

Facebook is a company that literally every kid is aware of. Its a household name. People from various age groups are there on this social media website. It has helped many in connecting with different people and also has helped some of the investors by earning them a good amount of money. This data set contains the details of the stock of Facebook Inc.

Content

This data set has 7 columns with all the necessary values such as opening price of the stock, the closing price of it, its highest in the day and much more. It has date wise data of the stock starting from 2012 to 2020(August).

[dataset PLOS ONE Facebook paper.xlsx]. (XLSX)

Gen Z and Millennials are the biggest social media users of all age groups.

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.

This dataset comprises 2,271 entries and provides insights into user interface (UI) and user experience (UX) preferences across various digital platforms. Key information includes user demographics (Name, Age, Gender) and platform preferences (e.g., Twitter, YouTube, Facebook, Website). It captures user experiences and satisfaction levels with various UI/UX elements such as color schemes, visual hierarchy, typography, multimedia usage, and layout design. The dataset also includes evaluations of mobile responsiveness, call-to-action buttons, form usability, feedback/error messages, loading speed, personalization, accessibility, and interactions (like scrolling behavior and gestures). Each UI/UX component is rated on a scale, allowing for quantitative analysis of user preferences and experiences, making this dataset valuable for research in user-centered design and usability optimization.

Dataset Card for PANDA

  Dataset Summary

PANDA (Perturbation Augmentation NLP DAtaset) consists of approximately 100K pairs of crowdsourced human-perturbed text snippets (original, perturbed). Annotators were given selected terms and target demographic attributes, and instructed to rewrite text snippets along three demographic axes: gender, race and age, while preserving semantic meaning. Text snippets were sourced from a range of text corpora (BookCorpus, Wikipedia, ANLI… See the full description on the dataset page: https://huggingface.co/datasets/facebook/panda.

The Multi-aspect Integrated Migration Indicators (MIMI) dataset is the result of the process of gathering, embedding and combining traditional migration datasets, mostly from sources like Eurostat and UNSD Demographic Statistics Database, and alternative types of data, which consists in multidisciplinary features and measures not typically employed in migration studies, such as the Facebook Social Connectedness Index (SCI). Its purpose is to exploit these novel types of data for: nowcasting migration flows and stocks, studying integration of multiple sources and knowledge, and investigating migration drivers.

The MIMI dataset is designed to have a unique pair of countries for each row. Each record contains country-to-country information about: migrations flows and stock their share, their strength of Facebook connectedness and other features, such as corresponding populations, GDP, coordinates, NET migration, and many others.

Methodology.

After having collected bilateral flows records about international human mobility by citizenship, residence and country of birth (available for both sexes and, in some cases, for different age groups), they have been merged together in order to obtain a unique dataset in which each ordered couple (country-of-origin, country-of-destination) appears once. To avoid duplicate couples, flow records have been selected by following this priority: first migration by citizenship, then migration by residence and lastly by country of birth.

The integration process started by choosing, collecting and meaningfully including many other indicators that could be helpful for the dataset final purpose mentioned above.

• International migration stocks (having a five-year range of measurement) for each couple of countries.
• Geographical features for each country: ISO3166 name and official name, ISO3166-1 alpha-2 and alpha-3 codes, continent code and name of belonging, latitude and longitude of the centroid, list of bordering countries, country area in square kilometres. Also, the following features have been included for each pair of countries: geodesic distance (in kilometres) computed between their respective centroids.

• Non-bidirectional migration measures for each country: total number of immigrants and emigrants for each year, NET migration and NET migration rate in a five-year range.

• Other multidisciplinary indicators (cultural, social, anthropological, demographical, historical features) related to each country: religion (single one or list), yearly GDP at PPP, spoken language (or list of languages), yearly population stocks (and population densities if available), number of Facebook users, percentage of Facebook users, cultural indicators (PDI, IDV, MAS, UAI, LTO). Also the following feature have been included for each pair of countries: Facebook Social Connectedness Index.

Once traditional and non-traditional knowledge is gathered and integrated, we move to the pre-processing phase where we manage the data cleaning, preparation and transformation. Here our dataset was subjected to various computational standard processes and additionally reshaped in the final structure established by our design choices.

The data quality assessment phase was one of the longest and most delicate, since many values were missing and this could have had a negative impact on the quality of the desired resulting knowledge. They have been integrated from additional sources such as The World Bank, World Population Review, Statista, DataHub, Wikipedia and in some cases extracted from Python libraries such as PyPopulation, CountryInfo and PyCountry.

The final dataset has the structure of a huge matrix having countries couples as index (uniquely identified by coupling their ISO 3166-1 alpha-2 codes): it comprises 28725 entries and 485 columns.

As of April 2024, almost 32 percent of global Instagram audiences were aged between 18 and 24 years, and 30.6 percent of users were aged between 25 and 34 years. Overall, 16 percent of users belonged to the 35 to 44 year age group.

              Instagram users

              With roughly one billion monthly active users, Instagram belongs to the most popular social networks worldwide. The social photo sharing app is especially popular in India and in the United States, which have respectively 362.9 million and 169.7 million Instagram users each.

              Instagram features

              One of the most popular features of Instagram is Stories. Users can post photos and videos to their Stories stream and the content is live for others to view for 24 hours before it disappears. In January 2019, the company reported that there were 500 million daily active Instagram Stories users. Instagram Stories directly competes with Snapchat, another photo sharing app that initially became famous due to it’s “vanishing photos” feature.
              As of the second quarter of 2021, Snapchat had 293 million daily active users.

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.