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).
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.
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These TikTok user statistics tell the whole story of the new social media giant and give you some insights into the app's future.
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The average adult TikTok user in America spends 33 minutes per day on the app.
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https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1842206%2Fd4a6033b6bd31af45d5175d02e697934%2FAPPLEAPPS2.png?generation=1700357122842963&alt=media" alt="">
These reviews are from Apple App Store
This dataset should paint a good picture on what is the public's perception of the apps over the years. Using this dataset, we can do the following
(AND MANY MORE!)
Images generated using Bing Image Generator
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Globally the average user spends 52 minutes on TikTok every day. About 90% of their worldwide users access TikTok on a daily basis.
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Teenagers make up the largest group of active users on TikTok.
https://cdla.io/sharing-1-0/https://cdla.io/sharing-1-0/
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.
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This dataset comprises user feedback data collected from 15 globally acclaimed mobile applications, spanning diverse categories. The included applications are among the most downloaded worldwide, providing a rich and varied source for analysis. The dataset is particularly suitable for Natural Language Processing (NLP) applications, such as text classification and topic modeling. List of Included Applications:
TikTok Instagram Facebook WhatsApp Telegram Zoom Snapchat Facebook Messenger Capcut Spotify YouTube HBO Max Cash App Subway Surfers Roblox Data Columns and Descriptions: Data Columns and Descriptions:
review_id: Unique identifiers for each user feedback/application review. content: User-generated feedback/review in text format. score: Rating or star given by the user. TU_count: Number of likes/thumbs up (TU) received for the review. app_id: Unique identifier for each application. app_name: Name of the application. RC_ver: Version of the app when the review was created (RC). Terms of Use: This dataset is open access for scientific research and non-commercial purposes. Users are required to acknowledge the authors' work and, in the case of scientific publication, cite the most appropriate reference: M. H. Asnawi, A. A. Pravitasari, T. Herawan, and T. Hendrawati, "The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling," in IEEE Access, vol. 11, pp. 130272-130286, 2023, doi: 10.1109/ACCESS.2023.3332644.
Researchers and analysts are encouraged to explore this dataset for insights into user sentiments, preferences, and trends across these top mobile applications. If you have any questions or need further information, feel free to contact the dataset authors.
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In 2020, TikTok brought in $33.4 billion in revenue.
This dataset encompasses social media exposure to sponsored posts, collected from over 150,000 triple-opt-in first-party U.S. Daily Active Users (DAU). Use it for measurement, attribution or brand lift surveying. Platforms covered include Facebook, TikTok, X, Instagram and YouTube.
Platform ad type coverage includes News Feed, Stories and In-Stream Videos on Facebook ; Feed and Reels on Instagram ; Feed on TikTok ; Timeline on X ; Pre-Roll on YouTube.
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Here are a few use cases for this project:
eCommerce Authentication: This model could be used in eCommerce platforms for verifying QR codes related to payment options like WeChat Pay and Alipay. By identifying these logos, the system could confirm the authenticity of the payment method.
Social Media Analysis: Researchers studying the prevalence and usage of different social media platforms in various contexts would find this model useful. By recognizing QR codes specific to WeChat (WeApp) and Douyin (Chinese version of TikTok), this model can provide valuable data about their usage and trends.
QR Code Categorization: This model can be used in a system that requires sorting or categorizing different types of QR codes. It could be useful in digital marketing strategy analyses or market research where differentiating sources of the QR codes (WeApp, Douyin, WordPress, etc.) is essential.
Digital Billboard Analysis: The "Weapp Qrcode" can be adopted for evaluating the presence of various logos and QR codes on digital billboards and advertisements. This information could be beneficial to marketers or city planners.
Advanced QR Scanner: Software development companies can use this model to create a more advanced QR scanner app. With its ability to identify specific QR code classes, users can gain quick insights about the source or company behind the scanned QR code.
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There are currently over 1.5 billion active users on TikTok worldwide.
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Regional TikTok user statistics differentiate significantly. Each major region has also experienced growth a different times.
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.
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Concise comparison of the top 10 YouTube alternatives for content creators in 2025. Covers monetization, audience size, and ideal use cases.
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TikTok has 136 million monthly active users in the US alone.
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TikTok has a significantly larger female user base globally.
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TikTok has risen through the ranks to become the 5th most popular social media network worldwide.
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.
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).