TikTok is the leading destination for short-form mobile video. The platform is built to help imaginations thrive. TikTok's mission is to create a place for inclusive, joyful, and authentic content–where people can safely discover, create, and connect.

This dataset captures the pulse of viral social media trends across TikTok, Instagram, Twitter, and YouTube. It provides insights into the most popular hashtags, content types, and user engagement levels, offering a comprehensive view of how trends unfold across platforms. With regional data and influencer-driven content, this dataset is perfect for:

• Trend analysis 🔍
• Sentiment modeling 💭
• Understanding influencer marketing 📈

Dive in to explore what makes content go viral, the behaviors that drive engagement, and how trends evolve on a global scale! 🌍

This dataset contains comprehensive information about TikTok posts, originally fetched from RapidAPI. It provides valuable insights into various aspects of TikTok content, including details about the videos, their creators, and audience engagement metrics.

Here's a breakdown of the columns included in this dataset:

video_id: A unique identifier for each TikTok video. author: The username or handle of the TikTok account that posted the video. description: The textual description or caption provided by the creator for the video. (Note: This column contains some missing values.) likes: The number of likes the video has received. comments: The number of comments on the video. shares: The number of times the video has been shared. plays: The total number of plays or views the video has accumulated. (Note: This column contains some missing values.) hashtags: A list of hashtags used in the video's description, which helps categorize content and improve discoverability. (Note: This column contains some missing values.) music: Information about the background music or sound used in the video. create_time: The timestamp indicating when the video was created or published. (Note: This column contains some missing values.) video_url: The direct URL to the TikTok video. fetch_time: The timestamp when the data for the video was fetched from the API. (Note: This column has a high number of missing values.) views: Another metric for the number of views. (Note: This column has a high number of missing values and appears to overlap with plays.) posted_time: The time the video was posted. (Note: This column has a high number of missing values and appears to overlap with create_time.) Potential Uses of This Dataset:

Content Analysis: Analyze popular TikTok content by examining descriptions, hashtags, and engagement metrics. Trend Identification: Identify trending topics, music, and creators on TikTok. Audience Engagement Studies: Understand how different types of content generate likes, comments, shares, and plays. Creator Analysis: Study the posting habits and performance of various TikTok creators. Social Media Research: Conduct research on the dynamics of content dissemination and user interaction on short-form video platforms. Notes on Data Quality:

The description, plays, hashtags, and create_time columns have some missing values, which may require handling (e.g., imputation or removal) depending on your analysis. The fetch_time, views, and posted_time columns are largely empty, suggesting they may not be reliable for comprehensive analysis. It is recommended to primarily rely on create_time for timestamps and plays for engagement metrics. This dataset can be a valuable resource for anyone looking to explore the vast and dynamic world of TikTok content and user engagement.

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.

Use our TikTok profiles dataset to extract business and non-business information from complete public profiles and filter by account name, followers, create date, or engagement score. You may purchase the entire dataset or a customized subset depending on your needs. Popular use cases include sentiment analysis, brand monitoring, influencer marketing, and more. The TikTok dataset includes all major data points: timestamp, account name, nickname, bio,average engagement score, creation date, is_verified,l ikes, followers, external link in bio, and more. Get your TikTok dataset today!

Description:

The "Daily Social Media Active Users" dataset provides a comprehensive and dynamic look into the digital presence and activity of global users across major social media platforms. The data was generated to simulate real-world usage patterns for 13 popular platforms, including Facebook, YouTube, WhatsApp, Instagram, WeChat, TikTok, Telegram, Snapchat, X (formerly Twitter), Pinterest, Reddit, Threads, LinkedIn, and Quora. This dataset contains 10,000 rows and includes several key fields that offer insights into user demographics, engagement, and usage habits.

Dataset Breakdown:

• Platform: The name of the social media platform where the user activity is tracked. It includes globally recognized platforms, such as Facebook, YouTube, and TikTok, that are known for their large, active user bases.

• Owner: The company or entity that owns and operates the platform. Examples include Meta for Facebook, Instagram, and WhatsApp, Google for YouTube, and ByteDance for TikTok.

• Primary Usage: This category identifies the primary function of each platform. Social media platforms differ in their primary usage, whether it's for social networking, messaging, multimedia sharing, professional networking, or more.

• Country: The geographical region where the user is located. The dataset simulates global coverage, showcasing users from diverse locations and regions. It helps in understanding how user behavior varies across different countries.

• Daily Time Spent (min): This field tracks how much time a user spends on a given platform on a daily basis, expressed in minutes. Time spent data is critical for understanding user engagement levels and the popularity of specific platforms.

• Verified Account: Indicates whether the user has a verified account. This feature mimics real-world patterns where verified users (often public figures, businesses, or influencers) have enhanced status on social media platforms.

• Date Joined: The date when the user registered or started using the platform. This data simulates user account history and can provide insights into user retention trends or platform growth over time.

Context and Use Cases:

• This synthetic dataset is designed to offer a privacy-friendly alternative for analytics, research, and machine learning purposes. Given the complexities and privacy concerns around using real user data, especially in the context of social media, this dataset offers a clean and secure way to develop, test, and fine-tune applications, models, and algorithms without the risks of handling sensitive or personal information.

Researchers, data scientists, and developers can use this dataset to:

• Model User Behavior: By analyzing patterns in daily time spent, verified status, and country of origin, users can model and predict social media engagement behavior.

• Test Analytics Tools: Social media monitoring and analytics platforms can use this dataset to simulate user activity and optimize their tools for engagement tracking, reporting, and visualization.

• Train Machine Learning Algorithms: The dataset can be used to train models for various tasks like user segmentation, recommendation systems, or churn prediction based on engagement metrics.

• Create Dashboards: This dataset can serve as the foundation for creating user-friendly dashboards that visualize user trends, platform comparisons, and engagement patterns across the globe.

• Conduct Market Research: Business intelligence teams can use the data to understand how various demographics use social media, offering valuable insights into the most engaged regions, platform preferences, and usage behaviors.

• Sources of Inspiration: This dataset is inspired by public data from industry reports, such as those from Statista, DataReportal, and other market research platforms. These sources provide insights into the global user base and usage statistics of popular social media platforms. The synthetic nature of this dataset allows for the use of realistic engagement metrics without violating any privacy concerns, making it an ideal tool for educational, analytical, and research purposes.

The structure and design of the dataset are based on real-world usage patterns and aim to represent a variety of users from different backgrounds, countries, and activity levels. This diversity makes it an ideal candidate for testing data-driven solutions and exploring social media trends.

Future Considerations:

As the social media landscape continues to evolve, this dataset can be updated or extended to include new platforms, engagement metrics, or user behaviors. Future iterations may incorporate features like post frequency, follower counts, engagement rates (likes, comments, shares), or even sentiment analysis from user-generated content.

By leveraging this dataset, analysts and data scientists can create better, more effective strategies ...

Use our TikTok Shop dataset to extract detailed e-commerce insights, including product names, prices, discounts, seller details, product descriptions, categories, customer ratings, and reviews. You may purchase the entire dataset or a customized subset tailored to your needs. Popular use cases include trend analysis, pricing optimization, customer behavior studies, and marketing strategy refinement. The TikTok Shop dataset includes key data points: product performance metrics, user engagement, customer reviews, and more. Unlock the potential of TikTok's shopping platform today with our comprehensive dataset!

This dataset supports research on how engagement with social media (Instagram and TikTok) was related to problematic social media use (PSMU) and mental well-being. There are three different files. The SPSS and Excel spreadsheet files include the same dataset but in a different format. The SPSS output presents the data analysis in regard to the difference between Instagram and TikTok users.

TikTok Video Analytics Dataset

Sample TikTok video dataset with comprehensive engagement metrics and metadata. Each row represents a single TikTok video with content and detailed analytics. This is a sample dataset. To access the full version or request any custom dataset tailored to your needs, contact DataHive at contact@datahive.ai.

  Files Included

train.csv – TikTok video analytics data

  What's included

Video URLs and identifiers Comprehensive engagement… See the full description on the dataset page: https://huggingface.co/datasets/datahiveai/Tiktok-Videos.

#Coronavirus on TikTok:

Examining Factors Related to Reception of Content

By [source]

About this dataset

This dataset explores various factors associated with the reception of COVID-19 related content on TikTok. It not only captures overall levels of user engagement such as likes, comments, and views but also explores source credibility including information from healthcare professionals, news sources, patients, and other outlets. It further dives into demographic factors such as gender and age range as well as content type like humor or provision of clinical instruction. Finally, it takes a look at elements such as description of risk factors & symptoms along with modes of transmission established by the posts in question and prevention that was discussed within them. Moreover, there is a discernment component that breaks down user perception - rating the posts for level of misinformation (moderate/high/low). All these measures combined provide insights into how users are engaging with COVID-19 related misinformation on TikTok

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How to use the dataset

This dataset contains user engagement data and measures of source credibility related to COVID-19 misinformation on TikTok. It can be used to examine the factors associated with content reception, such as views, likes, comments, as well as factors relating to credibility, demographics and content type.

Using this dataset: - Explore the columns available in the dataset. There are a number of columns that measure user engagement (views, likes and comments) as well as source credibility (official source, healthcare professional etc.), demographic factors (gender, age group etc.), and content type (humor etc). Get familiar with all these columns so that you know what information is available for analysis.
- Decide what kind of analysis you want to perform. You can use this data for exploratory or explanatory work - depending on your aims or research question. For example if you want to see how source credibility affects user engagement then you would need descriptive statistical techniques such as correlation tests or regression analyses etc., whereas if you just want to gain an overall understanding of patterns in this data then exploratory techniques such as cross tabulations may be more suitable.

Research Ideas

• Developing a predictive model to identify which demographic and source characteristics are correlated with high user engagement for COVID-related posts on TikTok (e.g. views, likes, and comments).
• Investigating the difference in user engagement for posts from healthcare professionals vs non-professional sources to compare how different types of content are received by users on TikTok.
• Analyzing the sentiment of words related to masks and tests in order to gain insights into how content about this topic is perceived by users on TikTok (i.e., positive or negative sentiment)

Acknowledgements

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

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: tiktok_data_open.csv | Column name | Description | |:-------------------------------|:------------------------------------------------------------------------| | views | Number of views for the video. (Integer) | | likes | Number of likes for the video. (Integer) | | comments | Number of comments for the video. (Integer) | | official_source | Whether the source of the video is an official source. (Boolean) | | pub_hcp | Whether the source of the video is a healthcare professional. (Boolean) | | pub_news | Whether the source of the video is a news source. (Boolean) | | pub_patient | Whether the source of the video is a patient. (Boolean) | | pub_other | Whether the source of the video is another source. (Boolean) | | female ...

Tiktok network graph with 5,638 nodes and 318,986 unique links, representing up to 790,599 weighted links between labels, using Gephi network analysis software. Source of: Peña-Fernández, Simón, Larrondo-Ureta, Ainara, & Morales-i-Gras, Jordi. (2022). Current affairs on TikTok. Virality and entertainment for digital natives. Profesional De La Información, 31(1), 1–12. https://doi.org/10.5281/zenodo.5962655 Abstract: Since its appearance in 2018, TikTok has become one of the most popular social media platforms among digital natives because of its algorithm-based engagement strategies, a policy of public accounts, and a simple, colorful, and intuitive content interface. As happened in the past with other platforms such as Facebook, Twitter, and Instagram, various media are currently seeking ways to adapt to TikTok and its particular characteristics to attract a younger audience less accustomed to the consumption of journalistic material. Against this background, the aim of this study is to identify the presence of the media and journalists on TikTok, measure the virality and engagement of the content they generate, describe the communities created around them, and identify the presence of journalistic use of these accounts. For this, 23,174 videos from 143 accounts belonging to media from 25 countries were analyzed. The results indicate that, in general, the presence and impact of the media in this social network are low and that most of their content is oriented towards the creation of user communities based on viral content and entertainment. However, albeit with a lesser presence, one can also identify accounts and messages that adapt their content to the specific characteristics of TikTok. Their virality and engagement figures illustrate that there is indeed a niche for current affairs on this social network.

Our TikTok Influencer Dataset provides comprehensive insights into influencer profiles, audience engagement, and market impact. This dataset is ideal for brands, marketers, and researchers looking to identify top-performing influencers, analyze engagement metrics, and optimize influencer marketing strategies on TikTok.

Key Features:

  Influencer Profiles: Access detailed influencer data, including profile name, bio, profile picture, and direct profile URL.
  Follower & Engagement Metrics: Track key performance indicators such as follower count, engagement rate, and interaction levels.
  Monetization Insights: Analyze influencer earnings with Gross Merchandise Value (GMV) and currency details.
  Category & Niche Segmentation: Identify influencers based on their associated product categories to match brand campaigns with relevant audiences.
  Contact Information: Retrieve available influencer email addresses for direct outreach and collaboration.


Use Cases:

  Influencer Discovery & Marketing: Find high-performing TikTok influencers for brand partnerships and sponsored campaigns.
  Competitive Analysis: Compare influencer engagement rates and audience reach to optimize marketing strategies.
  Market Research & Trend Analysis: Identify emerging influencers and track content trends within different product categories.
  Performance Benchmarking: Evaluate influencer success based on GMV, engagement rate, and follower growth.
  Lead Generation & Outreach: Use available contact details to connect with influencers for collaborations and brand promotions.



  Our TikTok Influencer Dataset is available in multiple formats (JSON, CSV, Excel) and can be delivered via 
  API, cloud storage (AWS, Google Cloud, Azure), or direct download. 
  Gain valuable insights into the TikTok influencer landscape and enhance your marketing strategies with high-quality, structured data.

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).

This repository contains all IDs for political TikTok posts used in the study “Toxic Politics and TikTok Engagement in the 2024 U.S. Election”, published in the Harvard Kennedy School Misinformation Review. The project investigates how political partisanship, toxicity, and topical content influence user engagement with TikTok videos during the 2024 U.S. presidential election cycle. If you use this dataset, please cite: Biswas, A., Javadian Sabet, A., & Lin, Y.-R. (2025). Toxic politics and TikTok engagement in the 2024 U.S. election. Harvard Kennedy School (HKS) Misinformation Review. https://doi.org/10.37016/mr-2020-181

Explore the fascinating world of TikTok with our comprehensive TikTok User Profiles Dataset. Whether you're a marketer, researcher, or enthusiast, this dataset provides a wealth of information on public TikTok profiles, allowing you to extract valuable business and non-business insights. You have the flexibility to purchase the complete dataset or tailor it to your specific needs by utilizing a range of filtering options.

Key Data Points:

• Timestamp
• Account name
• Nickname
• Bio
• Average engagement score
• Creation date
• Verification status
• Likes count
• Followers count
• External link in bio
• and many more

Popular Use Cases: Unleash the potential of this dataset for a variety of applications, including:

Sentiment Analysis: Gain deep insights into user sentiment by analyzing profiles' content, engagement, and interactions. Brand Monitoring: Track mentions of your brand, products, or services across TikTok, understanding how users perceive and engage with your offerings. Influencer Marketing: Identify potential influencers by assessing their follower count, engagement, and overall impact, helping you make informed collaboration decisions. Audience Insights: Understand your target audience by examining user bios, locations, and other profile details, aiding in tailoring your content and strategies.

Source: BrightData

Introducing a comprehensive and meticulously curated dataset: "European Interest Groups' Social Media Engagement Dataset." This dataset offers a panoramic view of the digital footprint and social media presence of various interest groups within Europe. Encompassing a diverse range of platforms including Twitter, Facebook, Instagram, TikTok, and YouTube. This are the variables:

1. Name: The name of the organization

2. twitter_link: The link of twitter if it is

3. facebook_link: The link of facebook if it is

4. instagram_link: The link of instagram if it is

5. tiktok_link: The link of tiktok if it is

6. linkedin_link: The link of linkedin if it is

7. youtube_link: The link of youtube if it is

With a focus on transparency and relevance, this dataset presents a wealth of information that delves into the strategies, content, and reach of interest groups across these dynamic online platforms. Researchers, policymakers, and analysts can explore trends, patterns, and correlations between online activities and real-world influence, shedding light on the evolving landscape of digital interaction within the realm of European interest groups.

Summary

This dataset contains TikTok comments and replies identified as antisemitic. This dataset contains metadata about each comment, such as user profile, engagement metrics, and geographical data, to support comprehensive analysis.

  Date Fields

The dataset is structured as a CSV file with the following columns: post_id: Unique numerical identifier for the TikTok post comment_id: Unique numerical identifier for the comment or reply parent_id: Reference to the comment_id… See the full description on the dataset page: https://huggingface.co/datasets/seanvelasco/tiktok-antisemitism.

A curated dataset of TikTok Mom creators with rich engagement metrics and post-level insights. Ideal for analyzing parenting and lifestyle content trends, influencer performance, and audience behavior—delivered in flexible, structured formats for easy integration.

The dataset includes engagement metrics such as the number of plays, likes, shares, and comments for all videos posted by news publishers on TikTok up to July 2023.

If you use this dataset in any publication or study, please cite: Cheng, Z., & Li, Y. (2023). Like, Comment, and Share on TikTok: Exploring the Effect of Sentiment and Second-Person View on the User Engagement with TikTok News Videos. Social Science Computer Review, 42(1), 201-223. https://doi.org/10.1177/08944393231178603

This dataset contains survey responses related to consumer behavior in TikTok live streaming commerce, with a particular focus on the beauty and personal care sector in Indonesia. The data was collected in 2025 through an online questionnaire distributed via Google Forms over a three-month period. A total of 390 respondents participated, all of whom had prior experience purchasing beauty and personal care products through TikTok live streams.

The dataset includes demographic information (such as age, gender, and education level) as well as variables measuring consumer perceptions and behaviors. These variables capture persuasive linguistic style of live stream hosts, customer trust, customer engagement, and purchase intention. All constructs were measured using a 5-point Likert scale.

The dataset is suitable for quantitative explanatory research and can be analyzed using advanced statistical techniques such as Partial Least Squares Structural Equation Modeling (PLS-SEM). It provides valuable insights into the influence of host communication styles on consumer trust, engagement, and purchase decisions in live streaming commerce. Researchers and practitioners can use this dataset to explore digital retail dynamics, customer behavior, and strategies for enhancing engagement and sales effectiveness in TikTok commerce.