During the 4th quarter 2024, approximately 153.06 million TikTok videos were removed from the platform, up by around four percent compared to the previous quarter. During the last measured quarter, the number of TikTok videos removed by automation represented approximately 81 percent of the total number of removed videos from the platform.

From March 2023 to August 2023, TikTok accounts posted on average *** thousand videos on Saturdays, as well as less than *** videos on Sundays. Wednesdays and Thursdays were the days of the week that content creators and influencers on TikTok posted the most, with *** thousand and *** thousand pieces of content published in these two days, respectively.

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 [Forthcoming dataset paper publication].

In 2024, TikTok accounts with up to *** views produced videos of approximately ** seconds on average. Small accounts produced videos of around ** seconds in length. Huge accounts, which had over ****** followers, produced content with a duration of around ** seconds on average as of the examined period. Overall, the length of the average TikTok videos across accounts of all sizes experienced ** ******** between 2023 and 2024.

Introduction

TikTok Statistics: Today, many social media platforms rule the world, and TikTok is one of them. Like the leading social media brands Facebook, Instagram, and YouTube, TikTok has similar functionality. Users can upload videos ranging from 3 seconds to 10 seconds, similar to short videos on other platforms. As mentioned in these TikTok Statistics, users in every generation think the platform is addictive.

Tiktok was developed by ByteDance, which is a Chinese internet company; therefore, since the lockdown, there have been a lot of controversies about blocking this platform. Let’s see what the future holds for this leading social media platform.

In 2024, TikTok accounts produced content of **** seconds length on average. This represents an increase compared to the previous year, when the average video on TikTok was ** seconds long. As TikTok tests long-form video content on its platform, internet users in the United States have reported the Chinese-developed platform as their favorite app to watch short-form video.

The TikHarm dataset is a curated collection of TikTok videos designed to train models for classifying harmful content. The dataset is in the format of UCF101, and it is specifically focused on content accessible to children, with the aim of distinguishing between different types of potentially harmful material.

Data Collection:

Data was gathered from TikTok, targeting videos that are accessible to children to ensure the dataset reflects the type of content they are likely to encounter.

Data Labeling:

Collected videos were manually labeled into four predefined categories: - Harmful Content: Videos that depict violence, dangerous actions that children might imitate, or other harmful behavior. - Adult Content: Videos containing sexual content or other material deemed inappropriate for children. - Safe: Videos that are appropriate and safe for children to view: popular cartoon, etc. - Suicide: Videos that depict, suggest, or discuss suicidal behavior or ideation.

Dataset Statistics:

These tables present the duration statistics for each subset and class within the TikHarm dataset.

This comprehensive dataset is invaluable for developing robust video classification models to automatically detect and categorize harmful content on social media platforms.

The dataset was originally obtained from TikTok's trending API by a GitHub user named Ivan Tran. It contains metadata on engagement with user-created videos and user profile data. The original create time is in Unix timecode format and is extracted directly from the video id number. TikTok's API has become much more difficult to access recently, so more current data is harder to obtain. The hashtags column contains lists.

YouTube Shorts and TikTok have become two of the most influential short-form video platforms in the world, shaping how users consume, share, and engage with content. From brand marketing to influencer careers, these platforms have redefined the digital media landscape, fueling trends, viral moments, and new monetization opportunities. Whether it’s...

TikTok-10M Dataset

  Dataset Description

TikTok-10M is a large-scale dataset containing 10 million short-form posts from TikTok, designed for video understanding, multimodal learning, and social media content analysis. The dataset was curated to bridge the gap between academic video datasets and actual user-generated content, providing researchers with authentic patterns and characteristics of modern short-form video content that dominates social media platforms.… See the full description on the dataset page: https://huggingface.co/datasets/The-data-company/TikTok-10M.

In 2023, TikTok accounts with up to *** followers views posted approximately **** videos per week. Their weekly posting frequency experienced a minor decrease in 2024, as tiny accounts posted around **** videos per week. Medium accounts - namely TikTok accounts between ***** and 10,000 followers posted around **** and **** videos per week in 2023 and 2024, respectively. Huge accounts, with over ****** followers, posted approximately six videos per week in 2024.

A sample of TikTok videos associated with the hashtag #coronavirus were downloaded on September 20, 2020. Misinformation was evaluated on a scale (low, medium, high) using a codebook developed by experts in infectious diseases. Multivariable modeling was used to evaluate factors associated with number of views and presence of user comments indicating intention to change behavior. Videos and related metadata were downloaded using a third-party TikTok Scraper using the search term #coronavirus. Videos were reviewed for content and data were entered on a spreadsheet.

We used TikTok’s built-in account analytics to download and record video and account metrics for the period between 10/8/2021 and 2/6/2022. We collected the following summary data for each individual video: video views, likes, comments, shares, total cumulative play time, average duration the video was watched, percentage of viewers who watched the full video, unique reached audience, and the percentage of video views by section (For You, personal profile, Following, hashtags).
We evaluated the “success” of videos based on reach and engagement metrics, as well as viewer retention (how long a video is watched). We used metrics of reach (number of unique users the video was seen by) and engagement (likes, comments, and shares) to calculate the engagement rate of each video. The engagement rate is calculated as the engagement parameter as a percentage of total reach (e.g., Likes / Audience Reached *100).

Introduction

TikTok vs Instagram Reels Statistics: In 2024, TikTok and Instagram Reels firmly dominated the short‑form video landscape through impressive user reach and engagement. As of April 2024, TikTok had amassed approximately 1.582 billion monthly active users, while Instagram reported around 2.00 billion monthly users (who all engage with Reels). TikTok users watched an average of 78 videos per day in 2023, rising to 92 per day by 2025. Engagement rates also revealed platform differences: Instagram Reels averaged about 1.48 percent in 2024, significantly higher than Instagram’s photo (0.70 percent) and carousel (0.99 percent) formats.

TikTok’s engagement for accounts with 100,000–500,000 followers reached 9.74 percent, compared to Reels’ 6.59 percent, and for accounts with over 10 million followers, the figures were 10.52 percent on TikTok and 8.77 percent on Reels. These metrics highlight TikTok’s broader audience and higher engagement potential, while Reels remain a highly competitive format within Instagram’s vast user base.

This article digs into the latest TikTok vs Instagram Reels statistics on the fronts of reach, user behaviour, demographics, engagement, and monetisation. All the numbers have been duly cited from industry sources and have been presented simply and well for easy readability.

USA

Replication Data for: How effective are TikTok misinformation debunking videos? Data, Preregistration, Qualtrics, Scripts, Videos

This is a dataset of videos and comments related to the invasion of Ukraine, published on TikTok by a number of users over the year of 2022. It was compiled by Benjamin Steel, Sara Parker and Derek Ruths at the Network Dynamics Lab, McGill University. We created this dataset to facilitate the study of TikTok, and the nature of social interaction on the platform relevant to a major political event.

The dataset has been released here on Zenodo: https://doi.org/10.5281/zenodo.7534952 as well as on Github: https://github.com/networkdynamics/data-and-code/tree/master/ukraine_tiktok

To create the dataset, we identified hashtags and keywords explicitly related to the conflict to collect a core set of videos (or ”TikToks”). We then compiled comments associated with these videos. All of the data captured is publically available information, and contains personally identifiable information. In total we collected approximately 16 thousand videos and 12 million comments, from approximately 6 million users. There are approximately 1.9 comments on average per user captured, and 1.5 videos per user who posted a video. The author personally collected this data using the web scraping PyTok library, developed by the author: https://github.com/networkdynamics/pytok.

Due to scraping duration, this is just a sample of the publically available discourse concerning the invasion of Ukraine on TikTok. Due to the fuzzy search functionality of the TikTok, the dataset contains videos with a range of relatedness to the invasion.

We release here the unique video IDs of the dataset in a CSV format. The data was collected without the specific consent of the content creators, so we have released only the data required to re-create it, to allow users to delete content from TikTok and be removed from the dataset if they wish. Contained in this repository are scripts that will automatically pull the full dataset, which will take the form of JSON files organised into a folder for each video. The JSON files are the entirety of the data returned by the TikTok API. We include a script to parse the JSON files into CSV files with the most commonly used data. We plan to further expand this dataset as collection processes progress and the war continues. We will version the dataset to ensure reproducibility.

To build this dataset from the IDs here:

Go to https://github.com/networkdynamics/pytok and clone the repo locally

Run pip install -e . in the pytok directory

Run pip install pandas tqdm to install these libraries if not already installed

Run get_videos.py to get the video data

Run video_comments.py to get the comment data

Run user_tiktoks.py to get the video history of the users

Run hashtag_tiktoks.py or search_tiktoks.py to get more videos from other hashtags and search terms

Run load_json_to_csv.py to compile the JSON files into two CSV files, comments.csv and videos.csv

If you get an error about the wrong chrome version, use the command line argument get_videos.py --chrome-version YOUR_CHROME_VERSION Please note pulling data from TikTok takes a while! We recommend leaving the scripts running on a server for a while for them to finish downloading everything. Feel free to play around with the delay constants to either speed up the process or avoid TikTok rate limiting.

Please do not hesitate to make an issue in this repo to get our help with this!

The videos.csv will contain the following columns:

video_id: Unique video ID

createtime: UTC datetime of video creation time in YYYY-MM-DD HH:MM:SS format

author_name: Unique author name

author_id: Unique author ID

desc: The full video description from the author

hashtags: A list of hashtags used in the video description

share_video_id: If the video is sharing another video, this is the video ID of that original video, else empty

share_video_user_id: If the video is sharing another video, this the user ID of the author of that video, else empty

share_video_user_name: If the video is sharing another video, this is the user name of the author of that video, else empty

share_type: If the video is sharing another video, this is the type of the share, stitch, duet etc.

mentions: A list of users mentioned in the video description, if any

The comments.csv will contain the following columns:

comment_id: Unique comment ID

createtime: UTC datetime of comment creation time in YYYY-MM-DD HH:MM:SS format

author_name: Unique author name

author_id: Unique author ID

text: Text of the comment

mentions: A list of users that are tagged in the comment

video_id: The ID of the video the comment is on

comment_language: The language of the comment, as predicted by the TikTok API

reply_comment_id: If the comment is replying to another comment, this is the ID of that comment

The date can be compiled into a user interaction network to facilitate study of interaction dynamics. There is code to help with that here: https://github.com/networkdynamics/polar-seeds. Additional scripts for further preprocessing of this data can be found there too.

A high-engagement dataset of TikTok posts with 50K+ plays. Includes video captions, play counts, likes, comments, shares, and creator details—ideal for trend analysis, viral content tracking, and performance benchmarking across TikTok creators and campaigns.

This graph contains weighted edges between names of celebrities (vertices) which have more than 60 percent of cosine similarity. Similarity info was taken from Gensim Fasttext model which was trained on texts (descriptions) for Tiktok videos.

From March 2023 to August 2023, TikTok videos with a duration of over ** seconds saw approximately *** percent engagement rate. Videos of a duration of less than ** seconds saw engagement rates of around *** percent, while videos with a length of between ** and ** seconds saw an engagement rate of **** percent.