100+ datasets found
  1. 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
    Explore at:
    .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.

  2. 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.

  3. 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

  4. 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.

  5. Instagram accounts with the most followers worldwide 2024

    • statista.com
    • es.statista.com
    + more versions
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    Stacy Jo Dixon, Instagram accounts with the most followers worldwide 2024 [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    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. Countries with the most Facebook users 2024

    • statista.com
    • ai-chatbox.pro
    • +1more
    + more versions
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    Stacy Jo Dixon, Countries with the most Facebook users 2024 [Dataset]. https://www.statista.com/topics/1164/social-networks/
    Explore at:
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    Which county has the most Facebook users?

                  There are more than 378 million Facebook users in India alone, making it the leading country in terms of Facebook audience size. To put this into context, if India’s Facebook audience were a country then it would be ranked third in terms of largest population worldwide. Apart from India, there are several other markets with more than 100 million Facebook users each: The United States, Indonesia, and Brazil with 193.8 million, 119.05 million, and 112.55 million Facebook users respectively.
    
                  Facebook – the most used social media
    
                  Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3,5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising.
    
                  Facebook usage by device
                  As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.
    
  7. Top 10 social media by active users

    • kaggle.com
    Updated Aug 15, 2024
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    Mahmoud Gamil (2024). Top 10 social media by active users [Dataset]. https://www.kaggle.com/datasets/mahmoudredagamail/number-of-monthly-active-users-worldwide
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 15, 2024
    Dataset provided by
    Kaggle
    Authors
    Mahmoud Gamil
    License

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

    Description

    Social Media has become a part of our day-to-day routine, keeping users from across the world well-connected through digital platforms. With each passing year, social media is evolving at a rapid speed. With each passing year, the number of social media users is increasing at an immersive speed. Reports also suggest the number of social media users will reach a milestone of 5.85 billion in 2027.

    In 2024, 62.6% of the world’s population will access social media, which clearly indicates the dominance of social media platforms in today’s world. In this article, we will examine social media statistics for 2024, uncovering monthly active users, daily time spent by users, most downloaded social media apps, etc.

  8. d

    Replication Data for: Social media usage and the differences between...

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
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    Sempala, Rayyah (2023). Replication Data for: Social media usage and the differences between different demographics [Dataset]. http://doi.org/10.5683/SP3/ET2X9D
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Sempala, Rayyah
    Description

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

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

    • statista.com
    • es.statista.com
    + more versions
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    Stacy Jo Dixon, Instagram: distribution of global audiences 2024, by gender [Dataset]. https://www.statista.com/topics/1164/social-networks/
    Explore at:
    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.
    
  10. f

    Data set belonging to Beyens et al. (2020). The effect of social media on...

    • uvaauas.figshare.com
    • narcis.nl
    bin
    Updated May 30, 2023
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    I. Beyens; J.L. Pouwels; I.I. van Driel; Loes Keijsers; P.M. Valkenburg (2023). Data set belonging to Beyens et al. (2020). The effect of social media on well-being differs from adolescent to adolescent [Dataset]. http://doi.org/10.21942/uva.12497990.v2
    Explore at:
    binAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    University of Amsterdam / Amsterdam University of Applied Sciences
    Authors
    I. Beyens; J.L. Pouwels; I.I. van Driel; Loes Keijsers; P.M. Valkenburg
    License

    http://rdm.uva.nl/en/support/confidential-data.htmlhttp://rdm.uva.nl/en/support/confidential-data.html

    Description

    This data set belongs to:Beyens, I., Pouwels, J. L., van Driel, I. I., Keijsers, L., & Valkenburg, P. M. (2020). The effect of social media on well-being differs from adolescent to adolescent. Scientific Reports. doi:10.1038/s41598-020-67727-7The design, sampling and analysis plan of the study are available on the Open Science Framework (OSF) at https://osf.io/nhks2.For more information, please contact the authors at i.beyens@uva.nl or info@project-awesome.nl.

  11. B

    Dataset: Decentralized Social Media Use and Users

    • borealisdata.ca
    • dataone.org
    Updated Aug 7, 2024
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    Anatoliy Gruzd; Alyssa Saiphoo; Philip Mai (2024). Dataset: Decentralized Social Media Use and Users [Dataset]. http://doi.org/10.5683/SP3/MJYGAR
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 7, 2024
    Dataset provided by
    Borealis
    Authors
    Anatoliy Gruzd; Alyssa Saiphoo; Philip Mai
    License

    https://borealisdata.ca/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.5683/SP3/MJYGARhttps://borealisdata.ca/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.5683/SP3/MJYGAR

    Dataset funded by
    Canada Research Chairs Program
    Description

    The dataset contains 31 transcribed and anonymized interviews of blockchain-based social media users. The dataset was collected during the summer of 2022 as part of a research project at the Social Media Lab at Toronto Metropolitan University. The dataset is available upon request for validation by peer-reviewers or other researchers in the field.

  12. m

    Abbreviated FOMO and social media dataset

    • figshare.mq.edu.au
    • researchdata.edu.au
    txt
    Updated May 30, 2023
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    Danielle Einstein; Carol Dabb; Madeleine Ferrari; Anne McMaugh; Peter McEvoy; Ron Rapee; Eyal Karin; Maree J. Abbott (2023). Abbreviated FOMO and social media dataset [Dataset]. http://doi.org/10.25949/20188298.v1
    Explore at:
    txtAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Macquarie University
    Authors
    Danielle Einstein; Carol Dabb; Madeleine Ferrari; Anne McMaugh; Peter McEvoy; Ron Rapee; Eyal Karin; Maree J. Abbott
    License

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

    Description

    This database is comprised of 951 participants who provided self-report data online in their school classrooms. The data was collected in 2016 and 2017. The dataset is comprised of 509 males (54%) and 442 females (46%). Their ages ranged from 12 to 16 years (M = 13.69, SD = 0.72). Seven participants did not report their age. The majority were born in Australia (N = 849, 89%). The next most common countries of birth were China (N = 24, 2.5%), the UK (N = 23, 2.4%), and the USA (N = 9, 0.9%). Data were drawn from students at five Australian independent secondary schools. The data contains item responses for the Spence Children’s Anxiety Scale (SCAS; Spence, 1998) which is comprised of 44 items. The Social media question asked about frequency of use with the question “How often do you use social media?”. The response options ranged from constantly to once a week or less. Items measuring Fear of Missing Out were included and incorporated the following five questions based on the APS Stress and Wellbeing in Australia Survey (APS, 2015). These were “When I have a good time it is important for me to share the details online; I am afraid that I will miss out on something if I don’t stay connected to my online social networks; I feel worried and uncomfortable when I can’t access my social media accounts; I find it difficult to relax or sleep after spending time on social networking sites; I feel my brain burnout with the constant connectivity of social media. Internal consistency for this measure was α = .81. Self compassion was measured using the 12-item short-form of the Self-Compassion Scale (SCS-SF; Raes et al., 2011). The data set has the option of downloading an excel file (composed of two worksheet tabs) or CSV files 1) Data and 2) Variable labels. References: Australian Psychological Society. (2015). Stress and wellbeing in Australia survey. https://www.headsup.org.au/docs/default-source/default-document-library/stress-and-wellbeing-in-australia-report.pdf?sfvrsn=7f08274d_4 Raes, F., Pommier, E., Neff, K. D., & Van Gucht, D. (2011). Construction and factorial validation of a short form of the self-compassion scale. Clinical Psychology and Psychotherapy, 18(3), 250-255. https://doi.org/10.1002/cpp.702 Spence, S. H. (1998). A measure of anxiety symptoms among children. Behaviour Research and Therapy, 36(5), 545-566. https://doi.org/10.1016/S0005-7967(98)00034-5

  13. Social Media vs Productivity

    • kaggle.com
    Updated May 15, 2025
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    Mahdi Mashayekhi (2025). Social Media vs Productivity [Dataset]. https://www.kaggle.com/datasets/mahdimashayekhi/social-media-vs-productivity/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 15, 2025
    Dataset provided by
    Kaggle
    Authors
    Mahdi Mashayekhi
    License

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

    Description

    📊 Social Media vs Productivity — Realistic Behavioral Dataset (30,000 Users)

    This dataset explores how daily digital habits — including social media usage, screen time, and notification exposure — relate to individual productivity, stress, and well-being.

    🔍 What’s Inside?

    The dataset contains 30,000 real-world-style records simulating behavioral patterns of people with various jobs, social habits, and lifestyle choices. The goal is to understand how different digital behaviors correlate with perceived and actual productivity.

    🧠 Why This Dataset is Valuable

    • Designed for real-world ML workflows
      Includes missing values, noise, and outliers — ideal for practicing data cleaning and preprocessing.

    • 🔗 High correlation between target features
      The perceived_productivity_score and actual_productivity_score are strongly correlated, making this dataset suitable for experiments in feature selection and multicollinearity.

    • 🛠️ Feature Engineering playground
      Use this dataset to practice feature scaling, encoding, binning, interaction terms, and more.

    • 🧪 Perfect for EDA, regression & classification
      You can model productivity, stress, or satisfaction based on behavior patterns and digital exposure.

    🧾 Columns & Feature Info

    Column NameDescription
    ageAge of the individual (18–65 years)
    genderGender identity: Male, Female, or Other
    job_typeEmployment sector or status (IT, Education, Student, etc.)
    daily_social_media_timeAverage daily time spent on social media (hours)
    social_platform_preferenceMost-used social platform (Instagram, TikTok, Telegram, etc.)
    number_of_notificationsNumber of mobile/social notifications per day
    work_hours_per_dayAverage hours worked each day
    perceived_productivity_scoreSelf-rated productivity score (scale: 0–10)
    actual_productivity_scoreSimulated ground-truth productivity score (scale: 0–10)
    stress_levelCurrent stress level (scale: 1–10)
    sleep_hoursAverage hours of sleep per night
    screen_time_before_sleepTime spent on screens before sleeping (hours)
    breaks_during_workNumber of breaks taken during work hours
    uses_focus_appsWhether the user uses digital focus apps (True/False)
    has_digital_wellbeing_enabledWhether Digital Wellbeing is activated (True/False)
    coffee_consumption_per_dayNumber of coffee cups consumed per day
    days_feeling_burnout_per_monthNumber of burnout days reported per month
    weekly_offline_hoursTotal hours spent offline each week (excluding sleep)
    job_satisfaction_scoreSatisfaction with job/life responsibilities (scale: 0–10)

    📌 Notes

    • Contains NaN values in critical columns (productivity, sleep, stress) for data imputation tasks
    • Includes outliers in media usage, coffee intake, and notification count
    • Target columns are strongly correlated for multicollinearity testing
    • Multi-purpose: regression, classification, clustering, visualization

    💡 Use Cases

    • Exploratory Data Analysis (EDA)
    • Feature engineering pipelines
    • Machine learning model benchmarking
    • Statistical hypothesis testing
    • Burnout and mental health prediction projects

    📥 Bonus

    👉 Sample notebook coming soon with data cleaning, visualization, and productivity prediction!

  14. Instagram: distribution of global audiences 2024, by age and gender

    • statista.com
    • es.statista.com
    + more versions
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    Stacy Jo Dixon, Instagram: distribution of global audiences 2024, by age and gender [Dataset]. https://www.statista.com/topics/1164/social-networks/
    Explore at:
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

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

                  Teens and social media
    
                  As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
                  Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.
    
  15. 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
    Explore at:
    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.

  16. Original social media data

    • figshare.com
    txt
    Updated May 13, 2023
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    Christine Tunkl (2023). Original social media data [Dataset]. http://doi.org/10.6084/m9.figshare.22816361.v1
    Explore at:
    txtAvailable download formats
    Dataset updated
    May 13, 2023
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Christine Tunkl
    License

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

    Description

    The hereby presented data are extracted from Meta, Tiktok and Twitter.

  17. f

    Data set belonging to Valkenburg et al. (2021). Social media use and...

    • uvaauas.figshare.com
    txt
    Updated May 30, 2023
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    P.M. Valkenburg; I. Beyens; J.L. Pouwels; I.I. van Driel; Loes Keijsers (2023). Data set belonging to Valkenburg et al. (2021). Social media use and adolescents’ self-esteem: Heading for a person-specific media effects paradigm [Dataset]. http://doi.org/10.21942/uva.19249145.v3
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    txtAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    University of Amsterdam / Amsterdam University of Applied Sciences
    Authors
    P.M. Valkenburg; I. Beyens; J.L. Pouwels; I.I. van Driel; Loes Keijsers
    License

    http://rdm.uva.nl/en/support/confidential-data.htmlhttp://rdm.uva.nl/en/support/confidential-data.html

    Description

    This data set belongs to:Valkenburg, P. M., Beyens, I., Pouwels, J. L., van Driel, I. I., & Keijsers, L. (2021). Social media use and adolescents' self-esteem: Heading for a person-specific media effects paradigm. Journal of Communication, 71(1), 56-78. https://doi.org/10.1093/joc/jqaa039More information about the study is available on the Open Science Framework (OSF), including the preregistration of the design and sampling plan (https://osf.io/327cx), the preregistration of the hypotheses and analysis plan (https://osf.io/peqa4), and all syntax files (https://osf.io/y3z7d).For more information, please contact the authors at p.m.valkenburg@uva.nl or info@project-awesome.nl.

  18. d

    Social Media Data | 30M+ YouTube Creators User Profile Dataset | 30M+...

    • datarade.ai
    Updated Oct 12, 2023
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    Webautomation (2023). Social Media Data | 30M+ YouTube Creators User Profile Dataset | 30M+ Influencers | Web-Scraped | GDPR compliant [Dataset]. https://datarade.ai/data-products/webautomation-youtube-creators-profile-dataset-10m-influen-webautomation
    Explore at:
    .json, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Oct 12, 2023
    Dataset authored and provided by
    Webautomation
    Area covered
    Guyana, Virgin Islands (British), Switzerland, Belize, Gibraltar, Lithuania, Portugal, Venezuela (Bolivarian Republic of), Bermuda, Estonia
    Description

    Extensive Creator Coverage: Our dataset includes a diverse range of YouTube content creators, spanning various genres, subscriber counts, and regions. Access information on creators from a wide spectrum of content categories.

    Creator Profiles: Explore detailed creator profiles, including biographies, subscriber counts, video counts, and contact information.

    Customizable Data Delivery: The dataset is available in flexible formats, such as CSV, JSON, or API integration, allowing seamless integration with your existing data infrastructure. Customize the data to meet your specific research and analysis needs.

  19. 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
    Explore at:
    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.

  20. m

    Graph-Based Social Media Data on Mental Health Topics

    • data.mendeley.com
    Updated Nov 4, 2024
    + more versions
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    Samuel Ady Sanjaya (2024). Graph-Based Social Media Data on Mental Health Topics [Dataset]. http://doi.org/10.17632/z45txpdp7f.2
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    Dataset updated
    Nov 4, 2024
    Authors
    Samuel Ady Sanjaya
    License

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

    Description

    This dataset is structured as a graph, where nodes represent users and edges capture their interactions, including tweets, retweets, replies, and mentions. Each node provides detailed user attributes, such as unique ID, follower and following counts, and verification status, offering insights into each user's identity, role, and influence in the mental health discourse. The edges illustrate user interactions, highlighting engagement patterns and types of content that drive responses, such as tweet impressions. This interconnected structure enables sentiment analysis and public reaction studies, allowing researchers to explore engagement trends and identify the mental health topics that resonate most with users.

    The dataset consists of three files: 1. Edges Data: Contains graph data essential for social network analysis, including fields for UserID (Source), UserID (Destination), Post/Tweet ID, and Date of Relationship. This file enables analysis of user connections without including tweet content, maintaining compliance with Twitter/X’s data-sharing policies. 2. Nodes Data: Offers user-specific details relevant to network analysis, including UserID, Account Creation Date, Follower and Following counts, Verified Status, and Date Joined Twitter. This file allows researchers to examine user behavior (e.g., identifying influential users or spam-like accounts) without direct reference to tweet content. 3. Twitter/X Content Data: This file contains only the raw tweet text as a single-column dataset, without associated user identifiers or metadata. By isolating the text, we ensure alignment with anonymization standards observed in similar published datasets, safeguarding user privacy in compliance with Twitter/X's data guidelines. This content is crucial for addressing the research focus on mental health discourse in social media. (References to prior Data in Brief publications involving Twitter/X data informed the dataset's structure.)

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Bright Data (2022). Social Media Datasets [Dataset]. https://brightdata.com/products/datasets/social-media
Organization logo

Social Media Datasets

Explore at:
.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.

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