How many people use social media?

              Social media usage is one of the most popular online activities. In 2024, over five billion people were using social media worldwide, a number projected to increase to over six billion in 2028.

              Who uses social media?
              Social networking is one of the most popular digital activities worldwide and it is no surprise that social networking penetration across all regions is constantly increasing. As of January 2023, the global social media usage rate stood at 59 percent. This figure is anticipated to grow as lesser developed digital markets catch up with other regions
              when it comes to infrastructure development and the availability of cheap mobile devices. In fact, most of social media’s global growth is driven by the increasing usage of mobile devices. Mobile-first market Eastern Asia topped the global ranking of mobile social networking penetration, followed by established digital powerhouses such as the Americas and Northern Europe.

              How much time do people spend on social media?
              Social media is an integral part of daily internet usage. On average, internet users spend 151 minutes per day on social media and messaging apps, an increase of 40 minutes since 2015. On average, internet users in Latin America had the highest average time spent per day on social media.

              What are the most popular social media platforms?
              Market leader Facebook was the first social network to surpass one billion registered accounts and currently boasts approximately 2.9 billion monthly active users, making it the most popular social network worldwide. In June 2023, the top social media apps in the Apple App Store included mobile messaging apps WhatsApp and Telegram Messenger, as well as the ever-popular app version of Facebook.

How much time do people spend on social media?

              As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 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 three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in
              the U.S. was just two 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.

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.

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

The dataset encompasses demographic, health, and mental health information of students from 48 different states in the USA, born between 1971 and 2003. It includes data on general health ratings, responses to the PHQ-9 depression screening tool, and the GAD-7 anxiety assessment tool. It details how often students experienced various mental health symptoms over the past two weeks, their depression severity scores, and anxiety severity scores. Also, it covers experiences of feeling overwhelmed, exhausted, and hopeless within the last 12 months, along with diagnoses of depression, therapy, and medication usage. The dataset also includes information on various medical conditions, student status (full-time or international), sex, and race.

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.

More than 100 social media channels and statistics for the National Archives and Records Administration.

The data from my thesis. This data was collected using the Lifeguide Software and exported onto SPSS following data collection. The data was collected from young people aged 11-18 years old to explore the impact of different types of social media use.

Facebook received 73,390 user data requests from federal agencies and courts in the United States during the second half of 2023. The social network produced some user data in 88.84 percent of requests from U.S. federal authorities. The United States accounts for the largest share of Facebook user data requests worldwide.

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.

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

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.

Internet Usage: Social Media Market Share: All Platforms: Youku data was reported at 0.000 % in 14 Apr 2024. This stayed constant from the previous number of 0.000 % for 13 Apr 2024. Internet Usage: Social Media Market Share: All Platforms: Youku data is updated daily, averaging 0.000 % from Apr 2024 (Median) to 14 Apr 2024, with 9 observations. The data reached an all-time high of 0.430 % in 10 Apr 2024 and a record low of 0.000 % in 14 Apr 2024. Internet Usage: Social Media Market Share: All Platforms: Youku data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Iran – Table IR.SC.IU: Internet Usage: Social Media Market Share.

During a January 2024 global survey among marketers, nearly 60 percent reported plans to increase their organic use of YouTube for marketing purposes in the following 12 months. LinkedIn and Instagram followed, respectively mentioned by 57 and 56 percent of the respondents intending to use them more. According to the same survey, Facebook was the most important social media platform for marketers worldwide.

Internet Usage: Social Media Market Share: All Platforms: Youku data was reported at 0.040 % in 02 May 2024. This records an increase from the previous number of 0.010 % for 01 May 2024. Internet Usage: Social Media Market Share: All Platforms: Youku data is updated daily, averaging 0.000 % from Jan 2024 (Median) to 02 May 2024, with 111 observations. The data reached an all-time high of 0.200 % in 26 Mar 2024 and a record low of 0.000 % in 30 Apr 2024. Internet Usage: Social Media Market Share: All Platforms: Youku data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s India – Table IN.SC.IU: Internet Usage: Social Media Market Share.

The purpose of the dataset is to enable the replication of results as reported in the article: Bonsaksen, T., Price, D., Lamph, G., Kabelenga, I., & Geirdal, A. Ø. (2025). Sleep problems were unrelated to social media use in the late COVID-19 pandemic phase: A cross-national study. PLOS ONE 20(1): e0318507. https://doi.org/10.1371/journal.pone.0318507. The data on sleep problems, psychosocial stress and social media use is uploaded as an SPSS file. Additional information to facilitate using the data can be found in the ReadMe file. The article aimed to explore the relationship between social media use and sleep problems in a cross-national sample two years after the pandemic began. It involved 1405 adults from four countries who completed an online survey. Statistical analyses included independent samples t-tests, Chi-Squared tests, and logistic regression. Among the 858 participants (61.1%) who reported recent sleep problems, 41.1% (353 individuals) attributed these issues to their COVID-19 experiences. Adjusting for age, gender, employment, and psychological distress showed that more hours of social media use were not significantly linked to sleep problems. However, being older, female, employed, and experiencing higher psychological distress were associated with more sleep issues.

The ANES 2020-2022 Social Media Study was a two-wave survey before and after the 2020 presidential election and a third survey following the 2022 midterm elections in the United States. Data from these surveys are available as a public use file from the American National Election Studies (ANES) website. The three questionnaires have largely the same content, affording repeated measures of the same constructs. The questionnaire covers voter turnout and candidate choice in the 2020 presidential primaries and general election, the coronavirus pandemic, the economy, feeling thermometers, feelings about how things are going in the country, trust in institutions, political knowledge and misinformation, political participation, political stereotyping, political diversity of social networks, and campaign/policy issues including health insurance, immigration, guns, and climate change.

Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4M+ companies, and is updated regularly to ensure we have the most up-to-date information.

We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

Products: API Suite Web UI Full and Custom Data Feeds

Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.

Social Media Disaster-Related Discussions

Detecting Relevant Content with Trusted Judgments

By CrowdFlower [source]

About this dataset

Welcome to the disaster tweets dataset! This collection of tweets holds a wealth of information about global disasters and their effects on people, governments, and organizations all over the world. With over 10,000 tweets collected and carefully annotated with labels of whether they reported an actual disaster or not, this dataset provides unique insight into what these events look like in terms of social media conversations.

This information is derived from a variety of key terms related to disaster events, such as “ablaze” and “pandemonium” which was used to gather each individual tweet for analysis. The columns for each tweet include detailed metadata about the user who posted it along with variables such as keyword relevance and location. Alongside all these attributes is the core text belonging to each individual tweet- giving you access to all sorts of stories from natural disasters, contagious disease outbreaks or conflicts between nations that can be found in one place!

So whatever you're looking for - whether it's observations about first-hand accounts or conducting research on public sentiment during a major event - this dataset offers you an invaluable source full of timely information that could potentially save lives down the line. So take your journey through this data now and embark upon discovering what devastation looks like through social media!

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How to use the dataset

This dataset contains tweets related to disaster events, including the keyword, location, text, tweetid and userid. It provides insights into how people interact with each other on social media during a disaster. Using this dataset you can gain valuable insight into the dynamics of online communication in disasters and provide an important point of reference for future disaster management initiatives.

Research Ideas

• Analyzing the effectiveness of disaster relief and humanitarian aid efforts, by mapping tweets against public data of areas affected by disasters and donations made to help those affected.
• Developing advanced statistical models to predict the magnitude and impact of an oncoming natural disaster using keyword analysis in social media posts related to past disasters.
• Creating text-based classifiers to accurately detect disaster-related tweets in real-time, allowing emergency services providers early warning signs before a potential event occurs

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: socialmedia-disaster-tweets-DFE.csv | Column name | Description | |:-----------------------|:-----------------------------------------------------------------------------------| | _golden | A boolean value indicating whether the tweet is a golden tweet or not. (Boolean) | | _unit_state | The state of the tweet (e.g. finalized, judged, etc.). (String) | | _trusted_judgments | The number of trusted judgments for the tweet. (Integer) | | _last_judgment_at | The date and time of the last judgment for the tweet. (DateTime) | | choose_one | The label assigned to the tweet (e.g. relevant, not relevant, etc.). (String) | | choose_one_gold | The gold label assigned to the tweet (e.g. relevant, not relevant, etc.). (String) | | keyword | The keyword associated with the tweet. (String) | | location | The location associated with the tweet. (String) | | text | The text content of the tweet. (String) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit CrowdFlower.

This data is an Excel file that has links to downloaded photographs posted to social media sites. There is a sheet with metadata in the file. This dataset is associated with the following publication: Angradi, T., J. Launspach, and R. Debbout. Determining preferences for ecosystem benefits in Great Lakes Areas of Concern from photographs posted to social media. JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 44(2): 340-351, (2018). NOTE: This dataset has been removed from public access due to revocation. Please refer inquiries regarding this dataset to the listed contact person.