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.

Facebook data is a valuable resource for businesses. It delivers essential information about your target audience. Over 2.9 billion people use Facebook worldwide. For example, you may learn about their demographics, hobbies, and online activities. Moreover, Facebook data may assist you in categorizing your target demographic. As a result, you may target your messaging to certain groups of people. This enhances the likelihood of your campaigns connecting with them. Furthermore, you may utilize Facebook data to monitor the effectiveness of your initiatives. This allows you to determine what is working and what is not. You can then make changes to enhance your outcomes. Facebook’s data is continually changing. Stay current with the newest trends and best practices. List To Data will help you get the most out of this important resource. Facebook number database is an invaluable tool for marketers looking to engage with their target demographic. This directory, often known as a contact list or dataset, contains crucial information such as user profiles and engagement metrics. This platform provides a wide reservoir of possible leads. Using this content, you may design tailored campaigns that increase engagement. Moving from general techniques to data-driven initiatives will help you achieve better outcomes. This information enables you to modify your messaging for higher response rates. Furthermore, this resource is updated regularly, guaranteeing that your campaigns always have new connections. Visit List To Data to get premium Facebook number databases and boost your company!

Access our extensive Facebook datasets that provide detailed information on public posts, pages, and user engagement. Gain insights into post performance, audience interactions, page details, and content trends with our ethically sourced data. Free samples are available for evaluation. Over 940M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:

Post ID Post Content & URL Date Posted Hashtags Number of Comments Number of Shares Likes & Reaction Counts (by type) Video View Count Page Name & Category Page Followers & Likes Page Verification Status Page Website & Contact Info Is Sponsored Post Attachments (Images/Videos) External Link Data And much more

Description:

The "Daily Social Media Active Users" dataset provides a comprehensive and dynamic look into the digital presence and activity of global users across major social media platforms. The data was generated to simulate real-world usage patterns for 13 popular platforms, including Facebook, YouTube, WhatsApp, Instagram, WeChat, TikTok, Telegram, Snapchat, X (formerly Twitter), Pinterest, Reddit, Threads, LinkedIn, and Quora. This dataset contains 10,000 rows and includes several key fields that offer insights into user demographics, engagement, and usage habits.

Dataset Breakdown:

• Platform: The name of the social media platform where the user activity is tracked. It includes globally recognized platforms, such as Facebook, YouTube, and TikTok, that are known for their large, active user bases.

• Owner: The company or entity that owns and operates the platform. Examples include Meta for Facebook, Instagram, and WhatsApp, Google for YouTube, and ByteDance for TikTok.

• Primary Usage: This category identifies the primary function of each platform. Social media platforms differ in their primary usage, whether it's for social networking, messaging, multimedia sharing, professional networking, or more.

• Country: The geographical region where the user is located. The dataset simulates global coverage, showcasing users from diverse locations and regions. It helps in understanding how user behavior varies across different countries.

• Daily Time Spent (min): This field tracks how much time a user spends on a given platform on a daily basis, expressed in minutes. Time spent data is critical for understanding user engagement levels and the popularity of specific platforms.

• Verified Account: Indicates whether the user has a verified account. This feature mimics real-world patterns where verified users (often public figures, businesses, or influencers) have enhanced status on social media platforms.

• Date Joined: The date when the user registered or started using the platform. This data simulates user account history and can provide insights into user retention trends or platform growth over time.

Context and Use Cases:

• This synthetic dataset is designed to offer a privacy-friendly alternative for analytics, research, and machine learning purposes. Given the complexities and privacy concerns around using real user data, especially in the context of social media, this dataset offers a clean and secure way to develop, test, and fine-tune applications, models, and algorithms without the risks of handling sensitive or personal information.

Researchers, data scientists, and developers can use this dataset to:

• Model User Behavior: By analyzing patterns in daily time spent, verified status, and country of origin, users can model and predict social media engagement behavior.

• Test Analytics Tools: Social media monitoring and analytics platforms can use this dataset to simulate user activity and optimize their tools for engagement tracking, reporting, and visualization.

• Train Machine Learning Algorithms: The dataset can be used to train models for various tasks like user segmentation, recommendation systems, or churn prediction based on engagement metrics.

• Create Dashboards: This dataset can serve as the foundation for creating user-friendly dashboards that visualize user trends, platform comparisons, and engagement patterns across the globe.

• Conduct Market Research: Business intelligence teams can use the data to understand how various demographics use social media, offering valuable insights into the most engaged regions, platform preferences, and usage behaviors.

• Sources of Inspiration: This dataset is inspired by public data from industry reports, such as those from Statista, DataReportal, and other market research platforms. These sources provide insights into the global user base and usage statistics of popular social media platforms. The synthetic nature of this dataset allows for the use of realistic engagement metrics without violating any privacy concerns, making it an ideal tool for educational, analytical, and research purposes.

The structure and design of the dataset are based on real-world usage patterns and aim to represent a variety of users from different backgrounds, countries, and activity levels. This diversity makes it an ideal candidate for testing data-driven solutions and exploring social media trends.

Future Considerations:

As the social media landscape continues to evolve, this dataset can be updated or extended to include new platforms, engagement metrics, or user behaviors. Future iterations may incorporate features like post frequency, follower counts, engagement rates (likes, comments, shares), or even sentiment analysis from user-generated content.

By leveraging this dataset, analysts and data scientists can create better, more effective strategies ...

Use our Facebook Profiles dataset to explore public profile details such as names, profile and cover photos, work history, education, and photo galleries. Common use cases include people and company research, influencer discovery, and academic studies of career and education signals on Facebook. Over 31M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:

Profile URL Profile Name Facebook Profile ID Profile Photo Cover Photo Work History (Title, Company, Company ID, Company URL, Start/End Dates) College Education (Name, ID, URL) High School Education (Name, ID, URL) Photo Galleries And much more

This is a codebook for data on the demographics of people who viewed, shared, and otherwise interacted with web pages (URLs) shared on Facebook, between January 1, 2017 and October 31, 2022. The data has about 68 million URLs, over 3.1 trillion rows, and over 71 trillion cell values. It results from a collaboration between Facebook and Social Science One (at IQSS at Harvard), originally prepared for Social Science One grantees and describes the "full" URLs dataset, including its scope, structure, and fields. This is version 10 of the codebook and data (released 4/13/2023), first described by Gary King and Nathaniel Persily at https://socialscience.one/blog/update-social-science-one.

Facebook probably needs no introduction; nonetheless, here is a quick history of the company. The world’s biggest and most-famous social network was launched by Mark Zuckerberg while he was a...

Facebook is becoming an essential tool for more than just family and friends. Discover how Cheltenham Township (USA), a diverse community just outside of Philadelphia, deals with major issues such as the Bill Cosby trial, everyday traffic issues, sewer I/I problems and lost cats and dogs. And yes, theft.

Communities work when they're connected and exchanging information. What and who are the essential forces making a positive impact, and when and how do conversational threads get directed or misdirected?

Use Any Facebook Public Group

You can leverage the examples here for any public Facebook group. For an example of the source code used to collect this data, and a quick start docker image, take a look at the following project: facebook-group-scrape.

Data Sources

There are 4 csv files in the dataset, with data from the following 5 public Facebook groups:

• Unofficial Cheltenham Township
• Elkins Park Happenings!
• Free Speech Zone
• Cheltenham Lateral Solutions
• Cheltenham Township Residents

post.csv

These are the main posts you will see on the page. It might help to take a quick look at the page. Commas in the msg field have been replaced with {COMMA}, and apostrophes have been replaced with {APOST}.

• gid Group id (5 different Facebook groups)
• pid Main Post id
• id Id of the user posting
• name User's name
• timeStamp
• shares
• url
• msg Text of the message posted.
• likes Number of likes

comment.csv

These are comments to the main post. Note, Facebook postings have comments, and comments on comments.

• gid Group id
• pid Matches Main Post identifier in post.csv
• cid Comment Id.
• timeStamp
• id Id of user commenting
• name Name of user commenting
• rid Id of user responding to first comment
• msg Message

like.csv

These are likes and responses. The two keys in this file (pid,cid) will join to post and comment respectively.

• gid Group id
• pid Matches Main Post identifier in post.csv
• cid Matches Comments id.
• response Response such as LIKE, ANGRY etc.
• id The id of user responding
• name Name of the user responding

member.csv

These are all the members in the group. Some members never, or rarely, post or comment. You may find multiple entries in this table for the same person. The name of the individual never changes, but they change their profile picture. Each profile picture change is captured in this table. Facebook gives users a new id in this table when they change their profile picture.

• gid Group id
• id Id of the member
• name Name of the member
• url URL of the member

Facebook Users Engagement Analysis Author: Tamara Banaim Dataset: Pseudo Facebook Dataset (Kaggle, uploaded to Hugging Face)

  Overview-

This project analyzes data from 99,003 Facebook users, focusing on demographic information and engagement metrics such as likes given, likes received, friend count, and account tenure. The analysis explores how age and user activity are related, and what factors influence engagement on the platform.

  Objective-

To examine how age and… See the full description on the dataset page: https://huggingface.co/datasets/tamarabanaim/facebook-users-data.

The Facebook Users by Country Data (Cleaned) dataset is a collection of information on Facebook users from different countries. The dataset contains five columns of data, which are named as follows:

• Names: This column contains the names of the countries for which the data is collected.
• Users: This column provides the number of Facebook users in millions for each respective country.
• Facebook_Users: This column shows the percentage of the total population of each country that uses Facebook.
• Date_of_Data: This column indicates the date on which the data was collected and compiled.
• Population: This column represents the total population of each country.

How you can use this Dataset?

The Facebook Users by Country Data (Cleaned) dataset can be used in several ways. Here are some potential use cases:

• Market Research: Marketers can use this dataset to identify markets with the highest concentration of Facebook users. This information can be used to target Facebook ads to specific regions, optimize social media campaigns, and determine which markets to expand into.

• Business Strategy: Businesses can use this dataset to identify potential markets for their products or services. By analyzing Facebook usage rates in different countries, businesses can identify countries with high engagement rates and target those markets.

• Social Media Analysis: Researchers can use this dataset to analyze social media behavior in different countries. By comparing Facebook usage rates across different countries, researchers can identify cultural and social differences that affect social media behavior.

This table includes platform data for Facebook participants in the Deactivation experiment. Each row of the dataset corresponds to data from a participant’s Facebook user account. Each column contains a value, or set of values, that aggregates log data for this specific participant over a certain period of time.

The number of Facebook users in the United States was forecast to continuously increase between 2024 and 2028 by in total 12.6 million users (+5.04 percent). After the ninth consecutive increasing year, the Facebook user base is estimated to reach 262.8 million users and therefore a new peak in 2028. Notably, the number of Facebook users of 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).

Do you need a data science project in finance domain?

Do you want to work on freshly collected dataset?

Do you need a newly created dataset to work on so that your project can help you get a job?

Do you also need an example on how to perform exploratory data analysis on time series data?

Then look no where. This is because you are at the right place and at the right time.

This dataset was collected using pandas_datareader library. Data source is stooq. This dataset consist of the stock price of Meta/Facebook from January, 2019 till April, 2023. This data can be used to perform time series analysis on any stock price such as open, close, high or low.

I have also created a notebook showing how you can perform exploratory data analysis on time series data.

TASK: 1. Determine moving average. 2. Determine weighted moving average. 3. Determine cumulative moving average. 4. Determine exponential moving average.

According to a September 2022 survey, 18 percent of social media users in the United States felt that Facebook protected their privacy and data, down from 27 percent in 2021. Overall, Millennials trusted the social media giant the most with their data in 2022, whilst Baby boomers were the least trusting, with just one in ten belonging to this generation feeling that Meta's Facebook protected their privacy and data.

As of October 2025, users aged 25 to 34 years made up Facebook's largest audience in the United States, accounting for **** percent of the social network's user base, with **** percent of those users being women. Overall, *** percent of users aged 35 to 44 years were women, and *** percent were men. How many people use Facebook in the United States? ******** is by far the most used social network in the world and finds a huge share of its audience in ****************** Facebook’s U.S. audience size comes second only to India. In 2023, there were over *** million Facebook users in the U.S. By 2028, it is estimated that around *** million people in the U.S. will be signed up for the platform. How do users in the United States view the platform? Although Facebook is widely used and very popular with U.S. consumers, there are issues of trust with its North American audience. As of November 2021, ** percent of respondents reported that they did not trust Facebook with their personal data. Despite having privacy doubts, a May 2022 survey found that ** percent of adults had a very favorable opinion of Facebook, and one-third held a somewhat positive view of the platform.

There were 10 363 000 Facebook users in United Arab Emirates in May 2020, which accounted for 96.8% of its entire population. The majority of them were men - 70.8%. People aged 25 to 34 were the largest user group (5 100 000). The highest difference between men and women occurs within people aged 25 to 34, where men lead by 3 600 000.

The metrics in this dataset measure users who viewed posts with links to civic news URLs. The dataset contains URL-level metrics from Facebook activity data for adult U.S. monthly active users, aggregated over the study period. Includes content views, audience size, content attributes, user attributes.

Quantifying global international mobility patterns can improve migration governance. Despite decades of calls by the international community to improve international migration statistics, the availability of timely and disaggregated data about long-term and short-term migration at the global level is still very limited. In this study, we investigate the feasibility of using non-traditional data sources to fill existing gaps in migration statistics. To this end, we use anonymised and publicly available data provided by Facebook’s advertising platform. Facebook’s advertising platform classifies its users as “lived in country X” if they previously lived in country X, and now live in a different country. Drawing on statistics about Facebook Network users (Facebook, Instagram, Messenger, and the Audience Network) who have lived abroad and applying a sample bias correction method, we estimate the number of Facebook Network (FN) “migrants” in 119 countries of residence and in two time periods by age, gender, and country of previous residence. The correction method estimates the probability of a person being a FN user based on age, sex, and country of current and previous residence. We further estimate the correlation between FN-derived migration estimates and reference official migration statistics. By comparing FN-derived migration estimates in two different time periods, January-February and August-September 2018, we successfully capture the increase in Venezuelan migrants in Colombia and Spain in 2018. FN-derived migration estimates cannot replace official migration statistics, as they are not representative, and the exact methods the FN uses for classifying its users are not known, and might change over time. However, after carefully assessing the validity of the FN-derived estimates by comparing them with data from reliable sources, we conclude that these estimates can be used for trend analysis and early-warning purposes.

Gain valuable insights with our comprehensive Social Media Dataset, designed to help businesses, marketers, and analysts track trends, monitor engagement, and optimize strategies. This dataset provides structured and reliable social media data from multiple platforms.

Dataset Features

User Profiles: Access public social media profiles, including usernames, bios, follower counts, engagement metrics, and more. Ideal for audience analysis, influencer marketing, and competitive research. Posts & Content: Extract posts, captions, hashtags, media (images/videos), timestamps, and engagement metrics such as likes, shares, and comments. Useful for trend analysis, sentiment tracking, and content strategy optimization. Comments & Interactions: Analyze user interactions, including replies, mentions, and discussions. This data helps brands understand audience sentiment and engagement patterns. Hashtag & Trend Tracking: Monitor trending hashtags, topics, and viral content across platforms to stay ahead of industry trends and consumer interests.

Customizable Subsets for Specific Needs Our Social Media Dataset is fully customizable, allowing you to filter data based on platform, region, keywords, engagement levels, or specific user profiles. Whether you need a broad dataset for market research or a focused subset for brand monitoring, we tailor the dataset to your needs.

Popular Use Cases

Brand Monitoring & Reputation Management: Track brand mentions, customer feedback, and sentiment analysis to manage online reputation effectively. Influencer Marketing & Audience Analysis: Identify key influencers, analyze engagement metrics, and optimize influencer partnerships. Competitive Intelligence: Monitor competitor activity, content performance, and audience engagement to refine marketing strategies. Market Research & Consumer Insights: Analyze social media trends, customer preferences, and emerging topics to inform business decisions. AI & Predictive Analytics: Leverage structured social media data for AI-driven trend forecasting, sentiment analysis, and automated content recommendations.

Whether you're tracking brand sentiment, analyzing audience engagement, or monitoring industry trends, our Social Media Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

There were 13 858 000 Facebook users in United Arab Emirates in May 2024. People aged 25 to 34 were the largest user group (5 900 000). The highest difference between men and women occurs within people aged 25 to 34, where men lead by 4 100 000.