Launched in 2016, TikTok rose to be one of the most popular social app and video platform for global users. In 2021, TikTok had approximately 656 million global users. This figure was projected to increase by around 15 percent year-over-year, reaching 755 million users in 2022. TikTok global installs peaked at the end of 2019, with the app amassing over 318 million downloads. During 2020 and 2021, TikTok download trends experienced a slower growth, amassing 173 million downloads from users worldwide during the last quarter of 2021.

Regional TikTok user statistics differentiate significantly. Each major region has also experienced growth a different times.

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.

In 2023, the number of TikTok users in Malaysia was estimated to reach around ** million. The number was forecast to continuously increase between 2024 and 2029. Based on the forecast, the number of TikTok users in Malaysia will reach **** million by 2029.User figures, shown here with regards to the platform TikTok, have been estimated by considering 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.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).

TikTok has risen through the ranks to become the 5th most popular social media network worldwide.

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.

📊 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

📌 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!

Context

US Supermarkets have seen a recent shortage of Feta Cheese due to a TikTok pasta that went viral. "https://www.fox5ny.com/news/viral-tiktok-video-recipe-prompts-feta-cheese-shortage"

The Brazilian music industry is already experiencing huge shifts in it's business model, TikTok changed young people playlists. Most of the biggest players in this market realized the day-light revolution of music going on, and are trying to influence as much as possible something many believe to be random: songs going viral.

Content

This data contains 10.000 rows, each describing a single video. Along with that, there are 14 columns: username, user id, video id, video desc, videotime, video length, video link, n likes, n shares, n comments, n plays, music name, music url

Acknowledgements

Thank you David Teather for developing a nice and easy-to-use API.

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.

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.

Please cite the following paper when using this dataset:

N. Thakur, “Five Years of COVID-19 Discourse on Instagram: A Labeled Instagram Dataset of Over Half a Million Posts for Multilingual Sentiment Analysis”, Proceedings of the 7th International Conference on Machine Learning and Natural Language Processing (MLNLP 2024), Chengdu, China, October 18-20, 2024 (Paper accepted for publication, Preprint available at: https://arxiv.org/abs/2410.03293)

Abstract

The outbreak of COVID-19 served as a catalyst for content creation and dissemination on social media platforms, as such platforms serve as virtual communities where people can connect and communicate with one another seamlessly. While there have been several works related to the mining and analysis of COVID-19-related posts on social media platforms such as Twitter (or X), YouTube, Facebook, and TikTok, there is still limited research that focuses on the public discourse on Instagram in this context. Furthermore, the prior works in this field have only focused on the development and analysis of datasets of Instagram posts published during the first few months of the outbreak. The work presented in this paper aims to address this research gap and presents a novel multilingual dataset of 500,153 Instagram posts about COVID-19 published between January 2020 and September 2024. This dataset contains Instagram posts in 161 different languages. After the development of this dataset, multilingual sentiment analysis was performed using VADER and twitter-xlm-roberta-base-sentiment. This process involved classifying each post as positive, negative, or neutral. The results of sentiment analysis are presented as a separate attribute in this dataset.

For each of these posts, the Post ID, Post Description, Date of publication, language code, full version of the language, and sentiment label are presented as separate attributes in the dataset.

The Instagram posts in this dataset are present in 161 different languages out of which the top 10 languages in terms of frequency are English (343041 posts), Spanish (30220 posts), Hindi (15832 posts), Portuguese (15779 posts), Indonesian (11491 posts), Tamil (9592 posts), Arabic (9416 posts), German (7822 posts), Italian (5162 posts), Turkish (4632 posts)

There are 535,021 distinct hashtags in this dataset with the top 10 hashtags in terms of frequency being #covid19 (169865 posts), #covid (132485 posts), #coronavirus (117518 posts), #covid_19 (104069 posts), #covidtesting (95095 posts), #coronavirusupdates (75439 posts), #corona (39416 posts), #healthcare (38975 posts), #staysafe (36740 posts), #coronavirusoutbreak (34567 posts)

The following is a description of the attributes present in this dataset

• Post ID: Unique ID of each Instagram post
• Post Description: Complete description of each post in the language in which it was originally published
• Date: Date of publication in MM/DD/YYYY format
• Language code: Language code (for example: “en”) that represents the language of the post as detected using the Google Translate API
• Full Language: Full form of the language (for example: “English”) that represents the language of the post as detected using the Google Translate API
• Sentiment: Results of sentiment analysis (using the preprocessed version of each post) where each post was classified as positive, negative, or neutral

Open Research Questions

This dataset is expected to be helpful for the investigation of the following research questions and even beyond:

1. How does sentiment toward COVID-19 vary across different languages?
2. How has public sentiment toward COVID-19 evolved from 2020 to the present?
3. How do cultural differences affect social media discourse about COVID-19 across various languages?
4. How has COVID-19 impacted mental health, as reflected in social media posts across different languages?
5. How effective were public health campaigns in shifting public sentiment in different languages?
6. What patterns of vaccine hesitancy or support are present in different languages?
7. How did geopolitical events influence public sentiment about COVID-19 in multilingual social media discourse?
8. What role does social media discourse play in shaping public behavior toward COVID-19 in different linguistic communities?
9. How does the sentiment of minority or underrepresented languages compare to that of major world languages regarding COVID-19?
10. What insights can be gained by comparing the sentiment of COVID-19 posts in widely spoken languages (e.g., English, Spanish) to those in less common languages?

All the Instagram posts that were collected during this data mining process to develop this dataset were publicly available on Instagram and did not require a user to log in to Instagram to view the same (at the time of writing this paper).

BackgroundThe development of short popular science video platforms helps people obtain health information, but no research has evaluated the information characteristics and quality of short videos related to cervical cancer. The purpose of this study was to evaluate the quality and reliability of short cervical cancer-related videos on TikTok and Kwai.MethodsThe Chinese keyword "cervical cancer" was used to search for related videos on TikTok and Kwai, and a total of 163 videos were ultimately included. The overall quality of these videos was evaluated by the Global Quality Score (GQS) and the modified DISCERN tool.ResultsA total of 163 videos were included in this study, TikTok and Kwai contributed 82 and 81 videos, respectively. Overall, these videos received much attention; the median number of likes received was 1360 (403–6867), the median number of comments was 147 (40–601), and the median number of collections was 282 (71–1296). In terms of video content, the etiology of cervical cancer was the most frequently discussed topic. Short videos posted on TikTok received more attention than did those posted on Kwai, and the GQS and DISCERN score of videos posted on TikTok were significantly better than those of videos posted on Kwai. In addition, the videos posted by specialists were of the highest quality, with a GQS and DISCERN score of 3 (2–3) and 2 (2–3), respectively. Correlation analysis showed that GQS was significantly correlated with the modified DISCERN scores (p

Aineistossa selvitetään 16-30 -vuotiaiden media-arkea nykypäivänä sekä heidän toiveitaan koskien tulevaisuuden mediaa. Kysely on osa Media-alan tutkimussäätiön rahoittamaa Tulevaisuuden media-arki nuorten kuvittelemana -hanketta, jonka toteuttivat yhteistyössä Tampereen yliopiston Comet-tutkimuskeskus sekä Aalto-yliopiston informaatioverkoston koulutusohjelma. Aluksi vastaajille esitettiin kysymyksiä koskien heidän käyttämiään mediateknisiä laitteita ja sosiaalisen median sovelluksia. Heiltä esimerkiksi tiedusteltiin, minkälaisia laitteita ja sovelluksia he säännöllisesti käyttävät sekä mihin tarkoitukseen. Seuraavaksi esitettiin kysymyksiä koskien vastaajien kokemuksia oman mediankäytön muuttamisesta sekä sen mahdollisesta rajoittamisesta. Edelleen vastaajia pyydettiin kuvailemaan, millä tapaa he ovat omaan mediankäyttöönsä tyytyväisiä tai tyytymättömiä. Kyselyn lopuksi pyrittiin vielä kartoittamaan vastaajien toiveita liittyen tulevaisuuden mediaan. Taustamuuttujina aineistossa ovat syntymävuosi, sukupuoli, maakunta, perhemuoto, koulutus ja pääasiallinen toiminta. The survey charted the everyday media use of 16-30-year-olds in Finland. The survey was conducted as part of the Young people imagining media(ted) futures: developing a methodology for change research project, which was a joint project between Research Centre Comet at Tampere University and the Information Networks Programme at Aalto University. First, the respondents were asked which electronic devices they had at home (e.g. smartphone, laptop, smart watch) and which devices they found the most important for their personal use. The respondents' use of various social media apps, such as Instagram, TikTok and Discord, was examined, and they were asked about the content they consumed online (e.g. news, social media posts, podcasts, music). Further questions surveyed what was most important to the respondents when using electronic media equipment and apps (e.g. having discussions with others, having a fun way to spend time, creating content of their own, making purchases online), whether the respondents' media use habits had changed in the past year, and whether they had ever tried to restrict their use of media. At the end of the survey, several open-ended questions were presented to the respondents regarding their satisfaction in their media use and their expectations and hopes for the media and electronic devices of the future. Background variables included the respondent's year of birth, gender, NUTS3 region of residence, household composition, level of education and economic activity and occupational status. Ei-todennäköisyysotanta: itsestään muotoutunut näyteNonprobability.Availability Non-probability: AvailabilityNonprobability.Availability Itsetäytettävä lomake: verkkolomakeSelfAdministeredQuestionnaire.CAWI

This dataset of 289,870 people sampled across TikTok, X, and Reddit reveals statistics of employee engagement in 2024 to find out whether employees consider themselves engaged, why they were engaged, what would make them more engaged, and to learn more about their demographics.

The table contains data from TikTok videos that portray dogs and their caregivers communicating with one another using soundboards. It includes the date each video was posted; the TikTok account on which each video appears; the description of each video by the account user; hashtags given to each video by the user; the number of views for each video; the number of likes, comments, and saves added to each video by its viewers; and the duration of each video. This data provided the authors of the study with a general overview of the talking-dog videos, including the videos' shared contemporariness, popularity and brevity. Identification of these qualities shaped the analysis of the videos, particularly with regard to their history and their figuration of human-canine relations. The paper concludes that, while the use of a soundboard may appear to offer direct insight into a dog's thoughts (historically precedented in canine performances dating back at least to the Middle Ages), this method paradoxically relies on extensive training and human interpretation, overshadowing other kinds of canine sonic expression. The authors suggest that such videos risk encouraging anthropomorphic views, making people less attentive to dogs’ nonverbal communication and more inclined to view them as infant-like rather than as distinct adult animals.

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.

As of April 2024, almost 32 percent of global Instagram audiences were aged between 18 and 24 years, and 30.6 percent of users were aged between 25 and 34 years. Overall, 16 percent of users belonged to the 35 to 44 year age group.

              Instagram users

              With roughly one billion monthly active users, Instagram belongs to the most popular social networks worldwide. The social photo sharing app is especially popular in India and in the United States, which have respectively 362.9 million and 169.7 million Instagram users each.

              Instagram features

              One of the most popular features of Instagram is Stories. Users can post photos and videos to their Stories stream and the content is live for others to view for 24 hours before it disappears. In January 2019, the company reported that there were 500 million daily active Instagram Stories users. Instagram Stories directly competes with Snapchat, another photo sharing app that initially became famous due to it’s “vanishing photos” feature.
              As of the second quarter of 2021, Snapchat had 293 million daily active users.

As of January 2024, #love was the most used hashtag on Instagram, being included in over two billion posts on the social media platform. #Instagood and #instagram were used over one billion times as of early 2024.

In 2023, Meta Platforms had a total annual revenue of over 134 billion U.S. dollars, up from 116 billion in 2022. LinkedIn reported its highest annual revenue to date, generating over 15 billion USD, whilst Snapchat reported an annual revenue of 4.6 billion USD.

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.