100+ datasets found
  1. c

    Social Media Usage Dataset(Applications)

    • cubig.ai
    Updated May 28, 2025
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    CUBIG (2025). Social Media Usage Dataset(Applications) [Dataset]. https://cubig.ai/store/products/321/social-media-usage-datasetapplications
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    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    CUBIG
    License

    https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

    Measurement technique
    Synthetic data generation using AI techniques for model training, Privacy-preserving data transformation via differential privacy
    Description

    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.

  2. Social Media Datasets

    • brightdata.com
    .json, .csv, .xlsx
    Updated Sep 7, 2022
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    Bright Data (2022). Social Media Datasets [Dataset]. https://brightdata.com/products/datasets/social-media
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    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    Sep 7, 2022
    Dataset authored and provided by
    Bright Datahttps://brightdata.com/
    License

    https://brightdata.com/licensehttps://brightdata.com/license

    Area covered
    Worldwide
    Description

    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.

  3. Social Media Usage Dataset(Applications)

    • kaggle.com
    Updated Oct 23, 2024
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    Bhadra Mohit (2024). Social Media Usage Dataset(Applications) [Dataset]. https://www.kaggle.com/datasets/bhadramohit/social-media-usage-datasetapplications/suggestions
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 23, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Bhadra Mohit
    License

    https://cdla.io/sharing-1-0/https://cdla.io/sharing-1-0/

    Description

    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.

  4. h

    Sentiment-Analysis-for-Social-Media-Monitoring

    • huggingface.co
    Updated Mar 6, 2025
    + more versions
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    Globose Technology Solutions (2025). Sentiment-Analysis-for-Social-Media-Monitoring [Dataset]. https://huggingface.co/datasets/globosetechnology12/Sentiment-Analysis-for-Social-Media-Monitoring
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    Dataset updated
    Mar 6, 2025
    Authors
    Globose Technology Solutions
    Description

    Problem Statement 👉 Download the case studies here A global consumer goods company struggled to understand customer sentiment across various social media platforms. With millions of posts, reviews, and comments generated daily, manually tracking and analyzing public opinion was inefficient. The company needed an automated solution to monitor brand perception, address negative feedback promptly, and leverage insights for marketing strategies. Challenge Analyzing social media sentiment posed… See the full description on the dataset page: https://huggingface.co/datasets/globosetechnology12/Sentiment-Analysis-for-Social-Media-Monitoring.

  5. Instagram accounts with the most followers worldwide 2024

    • statista.com
    • davegsmith.com
    Updated Jun 17, 2025
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    Stacy Jo Dixon (2025). Instagram accounts with the most followers worldwide 2024 [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Dataset updated
    Jun 17, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    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.
    
  6. m

    Survey Dataset on Face to Face Students' intention to use Social Media and...

    • data.mendeley.com
    Updated Jun 18, 2020
    + more versions
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    Akande Oluwatobi (2020). Survey Dataset on Face to Face Students' intention to use Social Media and Emerging Technologies for Continuous Learning [Dataset]. http://doi.org/10.17632/vb2m5x5xhr.2
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    Dataset updated
    Jun 18, 2020
    Authors
    Akande Oluwatobi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    One of the sectors that felt the impact of the Corona Virus Disease 2019 (COVID-19) pandemic was the educational sector. The outbreak led to the immediate closure of schools at all levels thereby sending billions of students away from their various institutions of learning. However, the shut down of academic institutions was not a total one as some institutions that were solely running online programmes were not affected. Those who were running face to face and online modes quickly switched over to the online mode. Unfortunately, institutions that have not fully embraced online mode of study were greatly affected. 85% of academic institutions in Nigeria are operating face to face mode of study, therefore, majority of Nigerian students at all levels were affected by the COVID-19 lockdown. Social media platforms and emerging technologies were the major backbones of institutions that are running online mode of study, therefore, this survey uses the unified theory of acceptance and use of technology (UTAUT) model to capture selected Face to face Nigerian University students accessibility, usage, intention and willingness to use these social media platforms and emerging technologies for learning. The challenges that could mar the usage of these technologies were also revealed. Eight hundred and fifty undergraduate students participated in the survey.

    The dataset includes the questionnaire used to retrieve the data, the responses obtained in spreadsheet format, the charts generated from the responses received, the Statistical Package of the Social Sciences (SPSS) file and the descriptive statistics for all the variables captured. This second version contains the reliability statistics of the UTAUT variables using Cronbach's alpha. This measured the reliability as well as the internal consistency of the UTAUT variables. This was measured in terms of the reliability statistics, inter-item correlation matrix and item-total statistics. Authors believed that the dataset will enhance understanding of how face to face students use social media platforms and how these platforms could be used to engage the students outside their classroom activities. Also, the dataset exposes how familiar face to face University students are to these emerging teaching and learning technologies.

  7. Impact of Digital Habits on Mental Health

    • kaggle.com
    Updated Jun 14, 2025
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    Shahzad Aslam (2025). Impact of Digital Habits on Mental Health [Dataset]. https://www.kaggle.com/datasets/zeesolver/mental-health
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 14, 2025
    Dataset provided by
    Kaggle
    Authors
    Shahzad Aslam
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    This dataset explores the relationship between digital behavior and mental well-being among 100,000 individuals. It records how much time people spend on screens, use of social media (including TikTok), and how these habits may influence their sleep, stress, and mood levels.

    It includes six numerical features, all clean and ready for analysis, making it ideal for machine learning tasks like regression or classification. The data enables researchers and analysts to investigate how modern digital lifestyles may impact mental health indicators in measurable ways.

    Dataset Applications

    • Quantify how screen‑time, TikTok use, or multi‑platform engagement statistically relate to stress, sleep loss, and mood.
    • Train regression or classification models that forecast stress level or mood score from real‑time digital‑usage metrics.
    • Feed user‑specific data into recommender systems that suggest screen‑time caps or bedtime routines to improve mental health.
    • Provide evidence for guidelines on youth screen‑time limits and platform moderation based on observed stress‑sleep trade‑offs.
    • Serve as a teaching dataset for EDA, feature engineering, and model evaluation in data‑science or psychology curricula.
    • Evaluate app interventions (e.g., screen‑time nudges) by comparing predicted versus actual post‑intervention stress or mood shifts.
    • Cluster individuals into digital‑behavior personas (e.g., “heavy late‑night scrollers”) to tailor mental‑health resources.
    • Generate synthetic time‑series scenarios (what‑if reductions in TikTok hours) to estimate downstream impacts on sleep and stress.
    • Use engineered features (ratio of TikTok hours to total screen‑time, etc.) in broader wellbeing models that include diet or exercise data.
    • Assess whether mental‑health prediction models remain accurate and unbiased across different screen‑time or platform‑use segments. # Column Descriptions
    • screen_time_hours – Daily total screen usage in hours across all devices.
    • social_media_platforms_used – Number of different social media platforms used per day.
    • hours_on_TikTok – Time spent on TikTok daily, in hours.
    • sleep_hours – Average number of sleep hours per night.
    • stress_level – Stress intensity reported on a scale from 1 (low) to 10 (high).
    • mood_score – Self-rated mood on a scale from 2 (poor) to 10 (excell # Inspiration This dataset was inspired by growing concerns about how screen time and social media affect mental health. It enables analysis of the links between digital habits, stress, sleep, and mood—encouraging data-driven solutions for healthier online behavior and emotional well-being. # Ethically Mined Data: This dataset has been ethically mined and synthetically generated without collecting any personally identifiable information. All values are artificial but statistically realistic, allowing safe use in academic, research, and public health projects while fully respecting user privacy and data ethics.
  8. B

    Data from: The State of Social Media in Canada 2022

    • borealisdata.ca
    • dataone.org
    Updated Sep 14, 2022
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    Philip Mai; Anatoliy Gruzd (2022). The State of Social Media in Canada 2022 [Dataset]. http://doi.org/10.5683/SP3/BDFE7S
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 14, 2022
    Dataset provided by
    Borealis
    Authors
    Philip Mai; Anatoliy Gruzd
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Canada
    Description

    The report provides a snapshot of the social media usage trends amongst online Canadian adults based on an online survey of 1500 participants. Canada continues to be one of the most connected countries in the world. An overwhelming majority of online Canadian adults (94%) have an account on at least one social media platform. However, the 2022 survey results show that the COVID-19 pandemic has ushered in some changes in how and where Canadians are spending their time on social media. Dominant platforms such as Facebook, messaging apps and YouTube are still on top but are losing ground to newer platforms such as TikTok and more niche platforms such as Reddit and Twitch.

  9. h

    social-media-instruction

    • huggingface.co
    Updated Jan 6, 2025
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    Bojan Jakimovski (2025). social-media-instruction [Dataset]. https://huggingface.co/datasets/Shekswess/social-media-instruction
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 6, 2025
    Authors
    Bojan Jakimovski
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Social Media Synthetic Dataset

      Description
    

    Topic: Social Media Posts and Interactions Domains: Social Media Platforms (Twitter, Facebook, Instagram) Focus: Synthetic collection of social media content and interactions Number of Entries: 500 Dataset Type: Raw Dataset Model Used: anthropic/claude-3-5-sonnet-20241022 Language: English Generated by: SynthGenAI Package

      Additional Information
    

    The dataset contains synthesized social media posts mimicking real… See the full description on the dataset page: https://huggingface.co/datasets/Shekswess/social-media-instruction.

  10. Data from: Social Media Engagement Dataset

    • kaggle.com
    Updated May 6, 2025
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    Subash Shanmugam (2025). Social Media Engagement Dataset [Dataset]. https://www.kaggle.com/datasets/subashmaster0411/social-media-engagement-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 6, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Subash Shanmugam
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This machine-generated dataset simulates social media engagement data across various metrics, including likes, shares, comments, impressions, sentiment scores, toxicity, and engagement growth. It is designed for analysis and visualization of trends, buzz frequency, public sentiment, and user behavior on digital platforms.

    The dataset can be used to:

    Identify spikes or drops in engagement

    Analyze changes in sentiment over time

    Build dashboards for digital trend tracking

    Test algorithms for sentiment analysis or trend prediction

  11. Instagram: distribution of global audiences 2024, by gender

    • statista.com
    • davegsmith.com
    Updated Jun 17, 2025
    + more versions
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    Stacy Jo Dixon (2025). Instagram: distribution of global audiences 2024, by gender [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Dataset updated
    Jun 17, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.

                  Instagram’s Global Audience
    
                  As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
                  As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.
    
                  Who is winning over the generations?
    
                  Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.
    
  12. Instagram: most popular posts as of 2024

    • statista.com
    • davegsmith.com
    Updated Jun 17, 2025
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    Stacy Jo Dixon (2025). Instagram: most popular posts as of 2024 [Dataset]. https://www.statista.com/topics/1164/social-networks/
    Explore at:
    Dataset updated
    Jun 17, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    Instagram’s most popular post

                  As of April 2024, the most popular post on Instagram was Lionel Messi and his teammates after winning the 2022 FIFA World Cup with Argentina, posted by the account @leomessi. Messi's post, which racked up over 61 million likes within a day, knocked off the reigning post, which was 'Photo of an Egg'. Originally posted in January 2021, 'Photo of an Egg' surpassed the world’s most popular Instagram post at that time, which was a photo by Kylie Jenner’s daughter totaling 18 million likes.
                  After several cryptic posts published by the account, World Record Egg revealed itself to be a part of a mental health campaign aimed at the pressures of social media use.
    
                  Instagram’s most popular accounts
    
                  As of April 2024, the official Instagram account @instagram had the most followers of any account on the platform, with 672 million followers. Portuguese footballer Cristiano Ronaldo (@cristiano) was the most followed individual with 628 million followers, while Selena Gomez (@selenagomez) was the most followed woman on the platform with 429 million. Additionally, Inter Miami CF striker Lionel Messi (@leomessi) had a total of 502 million. Celebrities such as The Rock, Kylie Jenner, and Ariana Grande all had over 380 million followers each.
    
                  Instagram influencers
    
                  In the United States, the leading content category of Instagram influencers was lifestyle, with 15.25 percent of influencers creating lifestyle content in 2021. Music ranked in second place with 10.96 percent, followed by family with 8.24 percent. Having a large audience can be very lucrative: Instagram influencers in the United States, Canada and the United Kingdom with over 90,000 followers made around 1,221 US dollars per post.
    
                  Instagram around the globe
    
                  Instagram’s worldwide popularity continues to grow, and India is the leading country in terms of number of users, with over 362.9 million users as of January 2024. The United States had 169.65 million Instagram users and Brazil had 134.6 million users. The social media platform was also very popular in Indonesia and Turkey, with 100.9 and 57.1, respectively. As of January 2024, Instagram was the fourth most popular social network in the world, behind Facebook, YouTube and WhatsApp.
    
  13. H

    Comprehensive Dataset of European Interest Groups Across Social Media...

    • dataverse.harvard.edu
    • portaldelainvestigacion.uma.es
    Updated Dec 29, 2023
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    Antonio Castillo Esparcia; Ana Almansa Martinez; Aritz Gorostiza Cervino (2023). Comprehensive Dataset of European Interest Groups Across Social Media Platforms: Twitter, Facebook, Instagram, TikTok, and YouTube [Dataset]. http://doi.org/10.7910/DVN/RRYJV7
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 29, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Antonio Castillo Esparcia; Ana Almansa Martinez; Aritz Gorostiza Cervino
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    YouTube
    Description

    Introducing a comprehensive and meticulously curated dataset: "European Interest Groups' Social Media Engagement Dataset." This dataset offers a panoramic view of the digital footprint and social media presence of various interest groups within Europe. Encompassing a diverse range of platforms including Twitter, Facebook, Instagram, TikTok, and YouTube. This are the variables: 1. Name: The name of the organization 2. twitter_link: The link of twitter if it is 3. facebook_link: The link of facebook if it is 4. instagram_link: The link of instagram if it is 5. tiktok_link: The link of tiktok if it is 6. linkedin_link: The link of linkedin if it is 7. youtube_link: The link of youtube if it is With a focus on transparency and relevance, this dataset presents a wealth of information that delves into the strategies, content, and reach of interest groups across these dynamic online platforms. Researchers, policymakers, and analysts can explore trends, patterns, and correlations between online activities and real-world influence, shedding light on the evolving landscape of digital interaction within the realm of European interest groups.

  14. Social Media Usage Survey

    • kaggle.com
    Updated Apr 8, 2025
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    SIDDHI PRIYA (2025). Social Media Usage Survey [Dataset]. https://www.kaggle.com/datasets/siddhipriya/social-media-usage-survey/suggestions
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    SIDDHI PRIYA
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Description

    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.

  15. Average daily time spent on social media worldwide 2012-2025

    • statista.com
    Updated Jun 19, 2025
    + more versions
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    Statista (2025). Average daily time spent on social media worldwide 2012-2025 [Dataset]. https://www.statista.com/statistics/433871/daily-social-media-usage-worldwide/
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    Dataset updated
    Jun 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    How much time do people spend on social media? As of 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 usageCurrently, 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 friends. Global impact of social mediaSocial 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 a polarization in politics and heightened everyday distractions.

  16. f

    Dataset Political Personalism in Social Media

    • figshare.com
    pdf
    Updated Aug 27, 2024
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    shahaf zamir (2024). Dataset Political Personalism in Social Media [Dataset]. http://doi.org/10.6084/m9.figshare.14073692.v1
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    pdfAvailable download formats
    Dataset updated
    Aug 27, 2024
    Dataset provided by
    figshare
    Authors
    shahaf zamir
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset covers aspects of online politics in 25 democracies: 15 relatively old established European democracies (Austria, Belgium, Denmark, Finland, France, Germany, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Sweden, Switzerland, United Kingdom); five non-European veteran democracies (Australia, Canada, Israel, Japan, New Zealand); two early (Portugal, Spain) and three late (Czech Republic, Hungary, Poland) third-wave (young) European democracies. The research population includes, in each country, parties that won 4% or more of the votes in two consecutive elections before April 2019 (a total of 141 parties and 145 leaders). The dataset includes external party level information such as performance in the last national elections, governmental status, party age, populism affiliation and leadership selection method. It also includes information related to the party leaders such as their term in leadership office and other formal positions. In addition it includes information about online activity mainly on the consumption (user related activities) of the parties and their leaders in Facebook and Twitter two of the most used social media platforms for political purposes.

  17. Data from: social media engagement

    • kaggle.com
    Updated Jul 2, 2025
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    Divya Raj Singh Shekhawat (2025). social media engagement [Dataset]. https://www.kaggle.com/datasets/divyaraj2006/social-media-engagement
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 2, 2025
    Dataset provided by
    Kaggle
    Authors
    Divya Raj Singh Shekhawat
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    About Dataset This dataset captures the pulse of viral social media trends across Facebook, Instagram and Twitter. It provides insights into the most popular hashtags, content types, and user engagement levels, offering a comprehensive view of how trends unfold across platforms. With regional data and influencer-driven content, this dataset is perfect for:

    Trend analysis 🔍 Sentiment modeling 💭 Understanding influencer marketing 📈 Dive in to explore what makes content go viral, the behaviors that drive engagement, and how trends evolve on a global scale! 🌍

  18. o

    Social Media Dataset of Covid-aware Publics

    • ordo.open.ac.uk
    csv
    Updated Sep 30, 2024
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    Christian Nold (2024). Social Media Dataset of Covid-aware Publics [Dataset]. http://doi.org/10.21954/ou.rd.27044467.v1
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    csvAvailable download formats
    Dataset updated
    Sep 30, 2024
    Dataset provided by
    The Open University
    Authors
    Christian Nold
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is a dataset of tweets by and about COVID-aware publics from the 'X' (Twitter) social media platform collected by the author. The dataset consists of 344 textual tweets regarding COVID-related material practices gathered during the research period Jan 2023 - Sep 2024, yet the dataset also includes tweets created before this date.The textual data has been rewritten to fully anonymise the people who made the tweets, and identifiable contexts have been removed. In addition, all date/time metadata and hashtags, as well as any attached images, have been removed. Square brackets have been used for editorial edits to obfuscate entities or add context to tweets. The dataset consists of a structured comma-separated text file that can be read in any spreadsheet software to maximise accessibility.The research dataset was created with Open university HREC approval: HREC/4557/Nold

  19. Reddit users in the United States 2019-2028

    • statista.com
    • ai-chatbox.pro
    Updated Jun 13, 2024
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    Statista Research Department (2024). Reddit users in the United States 2019-2028 [Dataset]. https://www.statista.com/topics/3196/social-media-usage-in-the-united-states/
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    Dataset updated
    Jun 13, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United States
    Description

    The number of Reddit users in the United States was forecast to continuously increase between 2024 and 2028 by in total 10.3 million users (+5.21 percent). After the ninth consecutive increasing year, the Reddit user base is estimated to reach 208.12 million users and therefore a new peak in 2028. Notably, the number of Reddit users of was continuously increasing over the past years.User figures, shown here with regards to the platform reddit, 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. Reddit users encompass both users that are logged in and those that are not.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).Find more key insights for the number of Reddit users in countries like Mexico and Canada.

  20. P

    Data from: iDRAMA-Scored-2024: A Dataset of the Scored Social Media Platform...

    • paperswithcode.com
    Updated May 15, 2024
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    Jay Patel; Pujan Paudel; Emiliano De Cristofaro; Gianluca Stringhini; Jeremy Blackburn (2024). iDRAMA-Scored-2024: A Dataset of the Scored Social Media Platform from 2020 to 2023 Dataset [Dataset]. https://paperswithcode.com/dataset/idrama-scored-2024
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    Dataset updated
    May 15, 2024
    Authors
    Jay Patel; Pujan Paudel; Emiliano De Cristofaro; Gianluca Stringhini; Jeremy Blackburn
    Description

    Online web communities often face bans for violating platform policies, encouraging their migration to alternative platforms. This migration, however, can result in increased toxicity and unforeseen consequences on the new platform. In recent years, researchers have collected data from many alternative platforms, indicating coordinated efforts leading to offline events, conspiracy movements, hate speech propagation, and harassment. Thus, it becomes crucial to characterize and understand these alternative platforms. To advance research in this direction, we collect and release a large-scale dataset from Scored -- an alternative Reddit platform that sheltered banned fringe communities, for example, c/TheDonald (a prominent right-wing community) and c/GreatAwakening (a conspiratorial community). Over four years, we collected approximately 57M posts from Scored, with at least 58 communities identified as migrating from Reddit and over 950 communities created since the platform's inception. Furthermore, we provide sentence embeddings of all posts in our dataset, generated through a state-of-the-art model, to further advance the field in characterizing the discussions within these communities. We aim to provide these resources to facilitate their investigations without the need for extensive data collection and processing efforts.

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CUBIG (2025). Social Media Usage Dataset(Applications) [Dataset]. https://cubig.ai/store/products/321/social-media-usage-datasetapplications

Social Media Usage Dataset(Applications)

Explore at:
Dataset updated
May 28, 2025
Dataset authored and provided by
CUBIG
License

https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

Measurement technique
Synthetic data generation using AI techniques for model training, Privacy-preserving data transformation via differential privacy
Description

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.

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