Market leader Facebook was the first social network to surpass one billion registered accounts and currently sits at more than three billion monthly active users. Meta Platforms owns four of the biggest social media platforms, all with more than one billion monthly active users each: Facebook (core platform), WhatsApp, Messenger, and Instagram. In the third quarter of 2023, Facebook reported around four billion monthly core Family product users. The United States and China account for the most high-profile social platforms Most top-ranked social networks with more than 100 million users originated in the United States, but services like Chinese social networks WeChat, QQ, or video-sharing app Douyin have also garnered mainstream appeal in their respective regions due to local context and content. Douyin’s popularity has led to the platform releasing an international version of its network, TikTok. How many people use social media? The leading social networks are usually available in multiple languages and enable users to connect with friends or people across geographical, political, or economic borders. In 2025, social networking sites are estimated to reach 5.44 billion users, and these figures are still expected to grow as mobile device usage and mobile social networks increasingly gain traction in previously underserved markets.

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 ...

This dataset provides detailed rankings and key metrics for 100+ social media platforms and sites in 2025. It includes information such as user base, popularity trends, and global reach. Ideal for analyzing social media growth, user engagement, and market trends. Whether you're a data scientist, marketer, or researcher, this dataset offers valuable insights into the evolving digital landscape.

This dataset contains 600 synthetic entries simulating social media activity across three major platforms: Twitter, Reddit, and Instagram. The data was generated to analyze trends, sentiments, and user engagement patterns based on hashtags and posts. It can be useful for researchers, data analysts, and machine learning enthusiasts interested in studying social media behavior.

Dataset Structure The dataset includes the following columns:

Date: The date of the post, ranging across a simulated timeline. Platform: The social media platform where the post was made (Twitter, Reddit, or Instagram). Hashtag: The main hashtag associated with the post, such as #AI, #MachineLearning, or #Python. Post Content: The text of the post, crafted to simulate common social media interactions. Sentiment: The sentiment of the post, classified as Positive, Neutral, or Negative. Likes: The number of likes the post received. Shares: The number of shares or retweets the post received. Potential Use Cases Sentiment analysis: Train machine learning models to detect sentiment in text. Hashtag popularity analysis: Determine which hashtags are most commonly used or generate the most engagement. Engagement trends: Explore correlations between post sentiment and engagement metrics (likes/shares). Platform comparison: Compare user behavior across different social media platforms. Acknowledgments This dataset is fully synthetic and was generated using Python. It does not contain any real user data and is intended for educational and research purposes.

During a 2025 survey among marketers worldwide, around 83 percent reported using Facebook for marketing purposes. Instagram and LinkedIn followed, respectively mentioned by 78 and 69 percent of the respondents. The global social media marketing segment According to the same study, 60 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 2025. 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.

How many people use social media? Social media usage is one of the most popular online activities. In 2025, over *** billion people were estimated to be using social media worldwide, a number projected to increase to over *** billion in 2030. 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 ** percent. This figure is anticipated to grow as less 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. The mobile-first market of 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 *** minutes per day on social media and messaging apps, an increase of ** 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 *** billion registered accounts and currently boasts approximately *** 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.

How does Truth Social compare to other social media platforms? There are around 2 million active Truth Social users.

1) Data Introduction • The Social Media Usage Dataset(Applications) features patterns and activity indicators that 1,000 users use seven major social media platforms, including Facebook, Instagram, and Twitter.

2) Data Utilization (1) Social Media Usage Dataset(Applications) has characteristics that: • This dataset provides different social media activity data for each user, including daily usage time, number of posts, number of likes received, and number of new followers. (2) Social Media Usage Dataset(Applications) can be used to: • Analysis of User Participation by Platform: You can analyze participation and popular trends by platform by comparing usage time and activity for each social media. • Establish marketing strategy: Based on user activity data, it can be used for targeted marketing, content production, and user retention strategies.

During a 2025 survey, ** percent of respondents from Nigeria stated that they used social media as a source of news. In comparison, just ** percent of Japanese respondents said the same. Large portions of social media users around the world admit that they do not trust social platforms either as media sources or as a way to get news, and yet they continue to access such networks on a daily basis. Social media: trust and consumption Despite the majority of adults surveyed in each country reporting that they used social networks to keep up to date with news and current affairs, a 2018 study showed that social media is the least trusted news source in the world. Less than ** percent of adults in Europe considered social networks to be trustworthy in this respect, yet more than ** percent of adults in Portugal, Poland, Romania, Hungary, Bulgaria, Slovakia and Croatia said that they got their news on social media. What is clear is that we live in an era where social media is such an enormous part of daily life that consumers will still use it in spite of their doubts or reservations. Concerns about fake news and propaganda on social media have not stopped billions of users accessing their favorite networks on a daily basis. Most Millennials in the United States use social media for news every day, and younger consumers in European countries are much more likely to use social networks for national political news than their older peers. Like it or not, reading news on social is fast becoming the norm for younger generations, and this form of news consumption will likely increase further regardless of whether consumers fully trust their chosen network or not.

This dataset provides granular, hourly influencer engagement metrics across major social media platforms, including detailed audience demographics and campaign associations. Brands and agencies can leverage this data for AI-powered analysis of peak activity times, audience response profiles, and campaign effectiveness, enabling data-driven marketing strategies and influencer selection.

This dataset provides detailed records of user interactions with social media posts, including likes, comments, and shares, across multiple platforms and campaigns. It enables in-depth analysis of engagement trends, audience demographics, and campaign effectiveness for social media analytics and marketing optimization.

Snapshot img

Social Networking Market Size 2025-2029

The social networking market size is forecast to increase by USD 312.3 billion, at a CAGR of 21.6% between 2024 and 2029.

Major Market Trends & Insights

North America dominated the market and accounted for a 41% growth during the forecast period.
By the Type - Advertising segment was valued at USD 80.70 billion in 2023
By the Distribution Channel - Google segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 318.56 billion
Market Future Opportunities: USD 312.30 billion 
CAGR : 21.6%
North America: Largest market in 2023

Market Summary

The market continues to expand its reach and influence across various industries, with businesses recognizing its potential for customer engagement and brand awareness. According to recent studies, there are approximately 4.66 billion active social media users worldwide, representing a 13% increase from 2020. This growth is driven by the increased internet penetration and the popularity of social media platforms for personal and professional use. Social media advertisements have become a significant revenue source, with businesses investing heavily in targeted campaigns to reach their audiences.
However, privacy concerns remain a challenge, with users increasingly cautious about sharing personal information online. Despite this, the market's continuous evolution and the emergence of new trends, such as live streaming and virtual events, ensure its ongoing relevance and importance for businesses.

What will be the Size of the Social Networking Market during the forecast period?

Explore market size, adoption trends, and growth potential for social networking market Request Free Sample

The market exhibits consistent growth, with current usage accounting for approximately 3.6 billion users worldwide, representing a significant 4.5% increase year-over-year. Looking ahead, industry experts anticipate a continued expansion, with projections indicating a 5.2% annual growth rate. Notably, mobile devices account for over 90% of social media usage, underscoring the importance of optimizing platforms for this medium. Furthermore, businesses increasingly leverage social networking for marketing purposes, with advertising revenue reaching an estimated USD 84.3 billion in 2021. In comparison, the time spent on social media platforms per day has risen by 45 minutes since 2019, highlighting the growing influence of these channels on consumer behavior.
This trend is further accentuated by the integration of advanced features, such as live streaming, video content, and AI-driven recommendations, which enhance user engagement and monetization opportunities.

How is this Social Networking Industry segmented?

The social networking industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Advertising
  In-app purchase
  Paid apps


Distribution Channel

  Google
  Apple
  App Store Distribution


Service

  Communication
  Entertainment
  Socialization
  Marketing
  Customer service


Platform

  Website-based
  Mobile apps
  Hybrid platforms


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    Spain
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The advertising segment is estimated to witness significant growth during the forecast period.

In the dynamic and evolving landscape of digital communication, the market continues to expand, driven by innovative technologies and user engagement. According to recent data, social networking platforms accounted for approximately 30% of the total time spent online in 2021, reflecting a significant 15% increase from the previous year. Furthermore, industry experts anticipate that social media usage will continue to grow, with an estimated 25% of the global population expected to use social media by 2025. Content moderation systems play a crucial role in ensuring a safe and inclusive online environment. These systems employ advanced techniques, such as natural language processing, conversational AI, and machine learning models, to filter out inappropriate content and maintain platform governance.

User engagement metrics, including time spent on platforms, user-generated content, and social interaction dynamics, are closely monitored to optimize user experience and foster community building strategies. Platform scalability and network security protocols are essential for accommodating the increasing user base and data privacy regulations. Spam filtering techniques and link pred

This dataset provides detailed, platform-specific metrics for social media influencers, including follower growth, engagement rates, post frequency, and brand partnerships. It enables marketers and analysts to identify trends, benchmark influencer performance, and optimize campaign strategies across various content categories and regions.

These datasets consist of qualitative data collected through semi-structured in-depth interviews as well as a focus group from three different companies with seven industry experts.The data collected was to address the use of social media to enhance organisational learning and also to address the gap that exists in terms of the integration of organisational learning (OL) and social media and also address the lack of guidelines for organisations that would like to implement the use of social media to facilitate OL. The data were triangulated by comparing the results from the three companies.

Currently, 2.7 billion people use at least one of the Facebook-owned social media platforms – Facebook, WhatsApp, and Instagram. Previous research investigating individual differences between users and non-users of these platforms has typically focused on one platform. However, individuals typically use a combination of Facebook-owned platforms. Therefore, we aim (1) to identify the relative prevalence of different patterns of social media use, and (2) to evaluate potential between-group differences in the distributions of age, gender, education, and Big Five personality traits. Data collection was performed using a cross-sectional design. Specifically, we administered a survey assessing participants’ demographic variables, current use of Facebook-owned platforms, and Big Five personality traits. In N = 3003 participants from the general population (60.67% females; mean age = 35.53 years, SD = 13.53), WhatsApp emerged as the most widely used application in the sample, and hence, has the strongest reach. A pattern consisting of a combined use of WhatsApp and Instagram appeared to be most prevalent among the youngest participants. Further, individuals using at least one social media platform were generally younger, more often female, and more extraverted than non-users. Small differences in Conscientiousness and Neuroticism also emerged across groups reporting different combinations of social media use. Interestingly, when examined as control variables, we found demographic characteristics partially accounted for differences in broad personality factors and facets across different patterns of social media use. Our findings are relevant to researchers carrying out their studies via social media platforms, as sample characteristics appear to be different depending on the platform used.

In 2008, the average human attention span was 12 seconds. Fast forward to 2025, and many studies suggest it's now hovering around 8 seconds, shorter than that of a goldfish. It’s no coincidence that during this same period, social media platforms surged to dominate how we consume content. Whether you're...

In the last two decades, social media usage has surged, reaching nearly five billion users worldwide in 2022. Unfortunately, there is a rise in mental health issues during that same time. Through a two-phase data analysis, this project studies the patterns of mental health influenced by social media. Analyzing data from 479 individuals across various platforms, the study employs K-means clustering to categorize mental health states into three groups, each indicating varying levels of professional/intervention needs. In the subsequent supervised learning phase, predictive models, including the Naive Bayes model with an under-sampled dataset and the Decision Tree model with an oversampled dataset, were developed to determine mental health categories, achieving an accuracy of 60.42%. These models, developed with comprehensive predictors, offer valuable insights for future research and the need for interventions addressing mental health challenges linked to social media use. Table 1 displays the variables, their descriptions, and value types. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13828311%2Fd9e0fb90d862e58aba958a14b3b8dcea%2FScreen%20Shot%202023-12-14%20at%2012.27.20%20PM.png?generation=1702578478575969&alt=media" alt="">

Phase I : Unsupervised Learning Techniques K-means Clustering Model

Using the elbow method pictured below in plot 1, we could visualize the optimal number of clusters (K), and then perform the K-means clustering with the optimal K. Several values for K were considered, and models were created for K = 2, 3, 4, 5, 6, 7, and 8, which were then compared. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13828311%2Fa77706842d108c7fbee363c1192b763a%2FScreen%20Shot%202023-12-14%20at%2012.08.01%20PM.png?generation=1702577407983039&alt=media" alt="">

In table 4 we can see the comparison of the bss/tss ratios. K = 3 is the last model with a significant jump and therefore is the optimal model. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13828311%2F9a44382d9c08a616bd0248f150b85526%2FScreen%20Shot%202023-12-14%20at%2012.08.20%20PM.png?generation=1702577436944201&alt=media" alt="">

In Table 5, we can observe the cluster centers for each variable within each cluster in the K-means clustering model with k = 3.https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13828311%2Fdf92bc28b65f67d88efa3b8a96295dcc%2FScreen%20Shot%202023-12-14%20at%2012.09.13%20PM.png?generation=1702577557552624&alt=media" alt="">

Based on the above cluster centers, we could interpret the cluster groups as shown in the table 6 below: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13828311%2F1d0624052cfc9ce50e7bc5b404d916d0%2FScreen%20Shot%202023-12-14%20at%2012.08.34%20PM.png?generation=1702577449886328&alt=media" alt="">

Phase II: Supervised Learning Techniques

Prediction Models

Data Input https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13828311%2F51672c4d16a801532a3ac8017cf72958%2FScreen%20Shot%202023-12-14%20at%2012.16.16%20PM.png?generation=1702577897888133&alt=media" alt=""> Above in Image A, we can see a sneak peek of the dataset with the new variable 'MHScore,' indicating mental health state cluster groups.

The outcome variable (MHScore) is categorical and multi-class (3 Levels: 1,2,3). Therefore, the implemented models include Naïve Bayes (NB), Support Vector Machines (SVM), SVM with parameter changes, Decision Trees, and Pruned Decision Trees.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13828311%2F06827fe209b78ffbddee69b272a8cdfc%2FScreen%20Shot%202023-12-14%20at%2012.20.41%20PM.png?generation=1702578062241650&alt=media" alt="">

Table 11 summarizes the results of the best model from each predictive machine learning technique for accuracy, balanced accuracy, sensitivity, specificity, and precision for each class. Each model was developed using the same predictors from the dataset, including age, gender, relationship status, occupation, organization of employment, social media usage, the number of social media platforms used, the hours spent on social media, and the frequency of social media use. The higher accuracy observed in both the under-sampled and oversampled datasets indicates the importance of class equality.

Currently, 2.7 billion people use at least one of the Facebook-owned social media platforms – Facebook, WhatsApp, and Instagram. Previous research investigating individual differences between users and non-users of these platforms has typically focused on one platform. However, individuals typically use a combination of Facebook-owned platforms. Therefore, we aim (1) to identify the relative prevalence of different patterns of social media use, and (2) to evaluate potential between-group differences in the distributions of age, gender, education, and Big Five personality traits. Data collection was performed using a cross-sectional design. Specifically, we administered a survey assessing participants’ demographic variables, current use of Facebook-owned platforms, and Big Five personality traits. In N = 3003 participants from the general population (60.67% females; mean age = 35.53 years, SD = 13.53), WhatsApp emerged as the most widely used application in the sample, and hence, has the strongest reach. A pattern consisting of a combined use of WhatsApp and Instagram appeared to be most prevalent among the youngest participants. Further, individuals using at least one social media platform were generally younger, more often female, and more extraverted than non-users. Small differences in Conscientiousness and Neuroticism also emerged across groups reporting different combinations of social media use. Interestingly, when examined as control variables, we found demographic characteristics partially accounted for differences in broad personality factors and facets across different patterns of social media use. Our findings are relevant to researchers carrying out their studies via social media platforms, as sample characteristics appear to be different depending on the platform used.

Social Media Software Market size was valued at USD 3.24 Billion in 2024 and is projected to reach USD 10.25 Billion by 2031, growing at a CAGR of 17.07% during the forecast period 2024-2031.

Social Media Software Market Drivers

Increasing Social Media Adoption: Growing number of social media users worldwide, driving the demand for software to manage and optimize social media presence.

Business Marketing and Branding: Businesses leveraging social media for marketing, branding, and customer engagement, necessitating advanced social media software tools.

Content Creation and Management: Rising need for tools that facilitate content creation, scheduling, and management across multiple social media platforms.

Analytics and Insights: Demand for analytics tools to measure social media performance, track metrics, and gain insights into audience behavior.

Customer Engagement and Support: Need for tools that enhance customer engagement and provide efficient customer support through social media channels.

Influencer Marketing: Growth of influencer marketing, requiring software to identify, manage, and track influencer collaborations and campaigns.

Ad Campaign Management: Increasing investment in social media advertising, driving the need for software that helps manage and optimize ad campaigns.

Social Media Listening: Importance of social media listening tools to monitor brand mentions, track sentiment, and manage reputation.

Integration with Other Tools: Integration capabilities with other business tools such as CRM, email marketing, and e-commerce platforms, enhancing the overall marketing strategy.

Regulatory Compliance: Need for tools that help ensure compliance with data privacy regulations and social media platform policies.

Over the last two observations, the reach by social network is forecast to significantly increase in all segments. Concerning the nine selected segments, the segment Facebook has the largest reach by social network with ****** million users. Contrastingly, Tumblr is ranked last, with **** million users. Their difference, compared to Facebook, lies at ****** million users. Find further statistics on other topics such as a comparison of the social network reach in Argentina and a comparison of the ad spending in the United States.The Statista Market Insights cover a broad range of additional markets.