This dataset captures insights from a survey on social media usage across diverse age groups and genders. It includes data on the most used platforms, daily screen time, reasons for usage, preferred content types, and how social media influences buying decisions. Additionally, it reflects users' concerns about privacy and their willingness to reduce usage. The dataset is useful for analyzing digital behavior, content preferences, and the social impact of online platforms. It can support research in marketing, psychology, and digital well-being, offering a snapshot of how people interact with and perceive social media in their daily lives.

A global survey conducted in the second quarter of 2025 found that the main reason for using social media was to stay in touch with friends and family, cited by **** percent of users. Nearly *** in **** respondents reported using social platforms to fill spare time, while fewer than *** in **** said they used them to follow celebrities and influencers. The most popular social network Facebook dominates the social media landscape. The world's most popular social media platform turned 20 in February 2024, and it continues to lead the way in terms of user numbers. As of February 2025, the social network had over ***** billion global users. YouTube, Instagram, and WhatsApp follow, but none of these well-known brands can surpass Facebook’s audience size. Moreover, as of the final quarter of 2023, there were almost **** billion Meta product users. Ever-evolving social media usage The utilization of social media remains largely gratuitous; however, companies have been encouraging users to become paid subscribers to reduce dependence on advertising profits. Meta Verified entices users by offering a blue verification badge and proactive account protection, among other things. X (formerly Twitter), Snapchat, and Reddit also offer users the chance to upgrade their social media accounts for a monthly free.

Context: This dataset offers insights into the usage patterns of social media apps for 1,000 users across seven popular platforms: Facebook, Instagram, Twitter, Snapchat, TikTok, LinkedIn, and Pinterest. It tracks various metrics such as daily time spent on the app, number of posts made, likes received, and new followers gained.

Dataset Features:

User_ID: Unique identifier for each user. App: The social media platform being used. Daily_Minutes_Spent: Total time a user spends on the app each day, ranging from 5 to 500 minutes. Posts_Per_Day: Number of posts a user creates per day, ranging from 0 to 20. Likes_Per_Day: Total number of likes a user receives on their posts each day, ranging from 0 to 200. Follows_Per_Day: The number of new followers a user gains daily, ranging from 0 to 50. Context & Use Cases: This dataset could be particularly useful for social media analysts, digital marketers, or researchers interested in understanding user engagement trends across different platforms. It provides insights into how much time users spend, how actively they post, and the level of engagement they receive (in terms of likes and followers).

Conclusion & Outcome: Analyzing this dataset could yield several outcomes:

Engagement Patterns: Identifying which platforms have higher engagement in terms of time spent or likes received. Active Users: Determining which users are the most active across various platforms based on the number of posts and followers gained. User Retention: Studying the correlation between time spent and follower growth, providing insight into user retention strategies for different platforms. Overall, the dataset allows for exploration of social media usage trends and helps drive decision-making for marketing strategies, content creation, and platform engagement.

In 2023, ** percent of respondents said they used Instagram to view official university accounts while researching colleges. ** percent also said they used Instagram to search for students at a university during their college search.

As of February 2025, the average daily social media usage of internet users worldwide amounted to 141 minutes per day, down from 143 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of 3 hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just 2 hours and 16 minutes. Global social media usage Currently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events and friends. Global impact of social media Social media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased polarization in politics, and heightened everyday distractions.

A line chart that shows % of U.S. adults who say they ever use …

Content

This dataset contains survey-based information about students’ social media usage habits and levels of addiction. It includes demographic details such as age, gender, and academic level, along with behavioral variables related to time spent on social media, preferred platforms, frequency of use, and purpose of engagement. The dataset also records indicators of addiction such as difficulty controlling usage, impact on sleep patterns, concentration in studies, emotional dependency, and feelings of anxiety or restlessness when not using social media. Each record represents an individual student’s response, providing a detailed view of how social media use varies across different student groups.

The data is structured in a clean tabular format, making it suitable for exploratory data analysis, visualization, and machine learning tasks. Researchers and students can use this dataset to study usage trends, classify addiction levels, predict behavioral outcomes, or analyze relationships between social media habits and academic or psychological factors.

Context

Social media has become an essential part of student life, offering opportunities for communication, entertainment, and learning. However, excessive use can lead to addiction, reduced academic performance, sleep disturbances, and mental health challenges. This dataset was collected to better understand the extent of social media dependency among students and to identify patterns that may contribute to unhealthy usage behavior. The dataset is useful for educators, psychologists, data scientists, and policymakers who are interested in studying digital behavior and its impact on young learners. It can support research on mental health awareness, digital well-being, and the development of intervention strategies to promote healthier social media habits among students.

The results might surprise you when looking at internet users that are active on social media in each country.

63.9% of the world’s total population is active on social media.

During a survey among internet users worldwide during the second quarter of 2025, an average of **** percent of global respondents said they used social media platforms to conduct research on brands. The top three markets with the highest share of internet users using social media for brand research were all African: Nigeria, Morocco, and Kenya all recorded shares above ** percent.

sleep duration

A line chart that shows % of all American adults and internet-using adults who use at least one social networking site

Which countries spent the most and least time on social media?

Overview

The Student Social Media & Relationships dataset contains anonymized records of students’ social‐media behaviors and related life outcomes. It spans multiple countries and academic levels, focusing on key dimensions such as usage intensity, platform preferences, and relationship dynamics. Each row represents one student’s survey response, offering a cross‐sectional snapshot suitable for statistical analysis and machine‐learning applications.

Scope & Coverage

• Population: Students aged 16–25 enrolled in high school, undergraduate, or graduate programs.
• Geography: Multi‐country coverage (e.g., Bangladesh, India, USA, UK, Canada, Australia, Germany, Brazil, Japan, South Korea).
• Timeframe: Data collected via a one‐time online survey administered in Q1 2025.
• Volume: Configurable sample sizes (e.g., 100, 500, 1,000 records) based on research needs.

Data Collection & Methodology

1. Survey Design: Questions adapted from validated scales on social‐media addiction (e.g., Bergen Social Media Addiction Scale) and relationship conflict indices.
2. Recruitment: Participants recruited through university mailing lists and social‐media platforms, ensuring diversity in academic level and country.

3. Data Quality Controls:

   • Validation: Mandatory fields and range checks (e.g., usage hours between 0–24).
   • De‐duplication: Removal of duplicate entries via unique Student_ID checks.
   • Anonymization: No personally identifiable information collected.

Key Variables

Potential Analyses

• Correlation Studies: Examine associations between daily usage hours and mental‐health score or sleep hours.
• Predictive Modeling: Build classifiers to predict relationship conflicts based on usage patterns and platform type.
• Clustering: Identify user segments (e.g., “high‐usage high‐stress” vs. “moderate‐usage balanced”) across countries.

Limitations

• Self‐Report Bias: All measures are self‐reported and may be subject to social‐desirability effects.
• Cross‐Sectional Design: One‐time survey prevents causal inference.
• Sampling Variability: Recruitment via online channels may underrepresent students with limited internet access.

Social Media User Behavior & Lifestyle – 1 Million Synthetic Users (Instagram 2025–2026 based)

This dataset contains 1,000,000+ fully synthetic user profiles that realistically simulate Instagram usage patterns combined with detailed demographic, lifestyle, health, and behavioral attributes.

All data is 100% synthetic — generated using statistical distributions and realistic correlations.
No real user data was used or collected. Perfectly safe for research, education, prototyping, and Kaggle competitions.

Dataset Overview

• Rows: 1,000,000 users
• Columns: 57
• File: instagram_usage_lifestyle_1million.csv (~250–350 MB uncompressed)
• License: CC0: Public Domain (use, modify, share freely)

Key Themes & Columns

Demographics & Background (19 columns)
age, gender, country, urban_rural, income_level, employment_status, education_level, relationship_status, has_children

Lifestyle & Health (10 columns)
exercise_hours_per_week, sleep_hours_per_night, diet_quality, smoking, alcohol_frequency, perceived_stress_score, self_reported_happiness, body_mass_index, blood_pressure_systolic, blood_pressure_diastolic, daily_steps_count

Daily/Weekly Habits (8 columns)
weekly_work_hours, hobbies_count, social_events_per_month, books_read_per_year, volunteer_hours_per_month, travel_frequency_per_year

Instagram Usage & Engagement (17 columns)
daily_active_minutes_instagram, sessions_per_day, posts_created_per_week, reels_watched_per_day, stories_viewed_per_day, likes_given_per_day, comments_written_per_day, dms_sent_per_week, dms_received_per_week, ads_viewed_per_day, ads_clicked_per_day, time_on_feed_per_day, time_on_explore_per_day, time_on_messages_per_day, time_on_reels_per_day, followers_count, following_count, notification_response_rate, average_session_length_minutes, content_type_preference, preferred_content_theme, privacy_setting_level, two_factor_auth_enabled, biometric_login_used, linked_accounts_count, subscription_status, user_engagement_score, account_creation_year, last_login_date, uses_premium_features

Built-in Realistic Correlations

• Higher perceived stress → increased daily active minutes & more reels/stories consumption
• Lower self-reported happiness → longer sessions & higher feed/reels time
• Younger age → significantly higher reels watched, posts created, follower growth
• More exercise & better sleep → slightly higher happiness & lower compulsive usage
• Higher income → increased likelihood of premium features & business accounts

Use Cases

• Exploratory Data Analysis (EDA) – discover links between screen time & well-being
• Predictive modeling – predict happiness/stress/sleep from usage patterns
• Clustering – identify user personas (doom-scroller, casual poster, aspiring influencer, etc.)
• A/B testing simulation – study behavioral effects
• Education & tutorials – great for teaching correlation, regression, feature engineering, large dataset handling
• Benchmarking – compare synthetic patterns vs real-world social media studies
• 100% synthetic – no real user data was accessed or used

Feedback, notebooks, or extensions welcome in the discussion tab.

This dataset provides comprehensive information about social media users and their activities across different platforms. It includes detailed records of user-generated content such as posts, captions, hashtags, likes, comments, shares, and reactions, along with engagement metrics that reflect how audiences interact with content. The dataset also captures patterns of user behavior, including posting frequency, interaction levels, and content popularity over time. It is designed to support in-depth analysis of social media trends, audience engagement, and digital communication behavior. Researchers and data analysts can use this dataset for exploratory data analysis, sentiment and trend analysis, and machine learning applications such as engagement prediction, user classification, and content recommendation. Overall, this dataset serves as a valuable resource for understanding social media dynamics and the impact of online interactions.

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

I’ve compiled a list of the latest social media user statistics showing just how big social media has become and where it’s likely to go in the future.

Between 2019, and 2024, global social media advertising spending skyrocketed by 140%, surpassing an estimated $230 billion in the latter year.

A line chart that shows Among all American adults, % who use social networking sites, by community type