We learn high fidelity human depths by leveraging a collection of social media dance videos scraped from the TikTok mobile social networking application. It is by far one of the most popular video sharing applications across generations, which include short videos (10-15 seconds) of diverse dance challenges as shown above. We manually find more than 300 dance videos that capture a single person performing dance moves from TikTok dance challenge compilations for each month, variety, type of dances, which are moderate movements that do not generate excessive motion blur. For each video, we extract RGB images at 30 frame per second, resulting in more than 100K images. We segmented these images using Removebg application, and computed the UV coordinates from DensePose.

Download TikTok Dataset:

Please use the dataset only for the research purpose.

The dataset can be viewed and downloaded from the Kaggle page. (you need to make an account in Kaggle to be able to download the data. It is free!)

The dataset can also be downloaded from here (42 GB). The dataset resolution is: (1080 x 604)

The original YouTube videos corresponding to each sequence and the dance name can be downloaded from here (2.6 GB).

These TikTok user statistics tell the whole story of the new social media giant and give you some insights into the app's future.

Globally the average user spends 52 minutes on TikTok every day. About 90% of their worldwide users access TikTok on a daily basis.

TikTok is developing into a key platform for news, advertising, politics, online shopping, and entertainment in Germany, with over 20 million monthly users. Especially among young people, TikTok plays an increasing role in their information environment. We provide a human-coded dataset of over 4,000 TikTok videos from German-speaking news outlets from 2023. The coding includes descriptive variables of the videos (e.g., visual style, text overlays, and audio presence) and theory-derived concepts from the journalism sciences (e.g., news values).

This dataset consists of every second video published in 2023 by major news outlets active on TikTok from Germany, Austria, and Switzerland. The data collection was facilitated with the official TikTok API in January 2024. The manual coding took place between September 2024 and December 2024. For a detailed description of the data collection, validation, annotation and descriptive analysis, please refer to:

Mayer, A.-T., Wedel, L., Batzner, J., Hendrickx, J., Bremer, E., Iwan, A., Stocker, V., & Ohme, J. (2025). News on TikTok: An Annotated Dataset of TikTok Videos from German-Speaking News Outlets in 2023. Proceedings of the Nineteenth International AAAI Conference on Web and Social Media, 19, forthcoming.

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).

Segmentation Full Body MADS Dataset

We took the MADS dataset as a basis (visal.cs.cityu.edu.hk/research/mads). We split the video into frames and highlight a person in each frame using Photoshop. A total of 1192 images and masks turned out.

💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on TrainingData to buy the dataset

SIMILAR DATASETS:

• Body Segmentation - 5,300 Photos
• Bald People Segmentation Dataset
• Segmentation Full Body TikTok Dancing Dataset
• Supervise.ly Filtered Segmentation Person Dataset
• Dataset of bald people, 5000 images

Image

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F618942%2Ffa5164bb22d59e7a3a45e3e9767e35e8%2FJazz_Jazz2_C0_00180.jpg?generation=1611186067659955&alt=media" alt="">

Content

The dataset includes 3 folders with photo: - collages - images with a labeled human figure - images - original images - masks - segmantation mask for the original photo

💴 Buy the Dataset: This is just an example of the data. Leave a request on https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset.

TrainingData provides high-quality data annotation tailored to your needs.

keywords: pose recognition database, pose detection dataset, pose estimation dataset, annotated body, pose annotations dataset, augmented reality, ar, 2d human movements, hpe dataset, martial arts dancing and sports dataset, body segmentation dataset, human part segmentation dataset, semantic segmentation, human body segmentation data, deep learning, computer vision, people images dataset, biometric data dataset, biometric dataset, images database, image-to-image, people segmentation, machine learning

Description

Tik Tak Tok - Est. 2023

  Model

HotshotXL

  Voice

Julian

  Orientation

Portrait

  Tags

Short Dancing

  Style

tiktok video, instagram, beautiful, sharp, detailed

  Music

mainstream pop music

  Prompt

A channel generating short vertical videos, between 20 seconds and 60 seconds Most videos are about people dancing, doing choregraphy, or talking selfies, filming their cats, daily life (eg. going to a cafe… See the full description on the dataset page: https://huggingface.co/datasets/jbilcke-hf/ai-tube-tik-tak-tok.

MASH: A Multiplatform Annotated Dataset for Societal Impact of Hurricane

Usage Notice

Humanitarian Classes

Bias Classes

Information Integrity Classes

Key Notes

1. This dataset is also available at https://huggingface.co/datasets/YRC10/MASH.
2. Version 1 is no longer available.

Name: LGBTQIAphobia_dataset_augmented_balanced
Description: Labeled dataset with phrases retrieved from different digital sources (X/twitter, Instagram, TikTok) containing diverse messages directed towards the LGBTQIA+ community. It has 1000 phrases classified as {Non-LGBTQIAphobic (0), LGBTQIAphobic (1)} . It is the balanced version of LGBTQIAphobia_dataset_augmented.
Language: Spanish
Format: CSV (UTF-8)
Structure: id; phrase; class {0,1}
Purpose: Be used for fine-tuned models that detect language offensive to Spanish or Latin LGBT communities in digital environments.
Sources: X/Twitter, Instagram, TikTok, Youtube comments
Size: 20Kb
Ethical considerations: This dataset was created strictly for academic and research purposes. We oppose any type of digital violence, in this case, against the LGBTQIA+ community. The person who was the target of the hate speech has been anonymised, and there is no intention to harm them in any way, either them or the person who delivered the speech. We prioritise the protection of the privacy and confidentiality of vulnerable individuals. To safeguard privacy, we carefully remove any identifying details, such as user IDs, phone numbers, and addresses, before sharing the data with our annotators. All the data we collect is from publicly available sources and does not contain any personal or sensitive information that may jeopardise anyone’s privacy. I request researchers to commit to abiding by ethical guidelines so as not to unnecessarily harm individuals.
¿How was it created?
- Starting recovery of discriminatory phrases for the LGBTQIA+ community from X/Twitter, Instagram, and Tiktok (197 phrases).
- Labelling by 3 raters as non-LGBTphobic (0) and LGBTphobic (1).
- Text augmentation was applied through backtranslation and random synonym replacement.
- Translating to Spanish part of McGiff, J., & Nikolov, N. S. (2024) dataset and was added under licence CC-BY-4.0
- To balance the majority class, we applied the undersampling technique.
- Finally, we obtained 1000 tagged phrases for version 1.0.2 of LGBTQIAphobia_augmented_balanced

Class distribution

class

 instances

0

513

1

487

where class is
0: non-lgbtphobic
1: lgbtphobic

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.

On July 30, 2020, the US President Donald Trump announced his plan to use executive orders or emergency economic powers to ban TikTok and disagreed with Microsoft’s acquisition of TikTok in the US. ByteDance, TikTok’s parent company, subsequently conducted several Chinese crisis communications on Toutiao — a platform owned by ByteDance that provides information to Chinese people. However, these announcements were reposted, sometimes rephrased or reformatted by third-party users on other Chinese social media platforms. These third-party users included both well-known influencers and general users. For example, the discussions became more salient on Sina Weibo, China’s largest online social media platform, than on any other platform, including Toutiao. Therefore, comparing crisis communications across different social media platforms is necessary. 50,702 data points were obtained for the entire dataset. Considering the efficiency of the manually labeled data, 8,793 data points were obtained after stratified random sampling of the dataset.

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.

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.

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

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

TikTok to Shake Up Southeast Asia with Billion-Dollar Investment

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Conjunto de respostas do formulário "O uso do Instagram e TikTok como mecanismos de busca". O formulário foi aplicado de forma online para centenas de pessoas de diferentes faixas etárias e níveis de escolaridade com o intuito de identificar o comportamento de busca dos usuários no Instagram e TikTok em comparação à Pesquisa Google. No total, foram obtidas 231 respostas válidas e todas elas estão inclusas neste arquivo de forma anonimizada. O questionário foi aplicado via Google Forms, se mantendo apto para o recolhimento de respostas do dia 20 de julho de 2024 até 27 de julho de 2024.

Dataset from the form "The use of Instagram and TikTok as search engines." The form was administered online to hundreds of individuals from different age groups and educational levels, aiming to identify users' search behavior on Instagram and TikTok compared to Google Search. In total, 231 valid responses were collected, all of which are included in this file in an anonymized format. The questionnaire was administered via Google Forms and remained open for responses from July 20, 2024, to July 27, 2024.

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.

The number of LinkedIn users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 1.5 million users (+4.51 percent). After the eighth consecutive increasing year, the LinkedIn user base is estimated to reach 34.7 million users and therefore a new peak in 2028. User figures, shown here with regards to the platform LinkedIn, 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.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).

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.