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

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!

This is the Dataset of popular hashtags on TikTok, this includes the author name, author id, author signature, comment count, hashtags details, URL, share count, hashtags which i scrape are meme, funny, humor, comedy, education, lol, dance, song, music, etc.

his dataset contains a large collection of TikTok video metadata fetched using the TikTok Scraper API. It includes videos from multiple regions (e.g., US, India,) and categories (e.g., fyp, dance, comedy, food, travel, etc.). Each video entry

provides detailed information such as:

Video ID: Unique identifier for the video. Region: The region where the video is popular. Category: The keyword/category used to fetch the video (e.g., dance, comedy). Title: The title of the video. Duration: The length of the video in seconds. Play URL: Direct link to the video. Watermarked URL: Link to the watermarked version of the video. Cover Image: URL of the video's cover image. Music URL: Link to the music used in the video. Timestamp: The date and time when the data was fetched.

How This Dataset Can Be Helpful

Trend Analysis: Analyze trending videos across different regions and categories. Identify patterns in video popularity based on region, duration, or category.

Machine Learning: Train models to predict video popularity based on features like duration, region, and category. Build recommendation systems for TikTok videos.

Content Moderation: Use the dataset to analyze video content for moderation purposes.

Sentiment Analysis: Perform sentiment analysis on video titles to understand user preferences.

Cross-Region Insights: Compare video trends across different regions to understand cultural differences.

How to Use This Dataset Filter by Region: Analyze videos from a specific region (e.g., US or India).

Filter by Category: Focus on videos from a specific category (e.g., dance or comedy).

Trend Analysis: Identify trending videos based on timestamp and region.

Machine Learning: Use the dataset to train models for video popularity prediction or recommendation systems.

The Excel data titled “TikTok’s User Comment on Skincare Product” contains 200 user comments regarding consumers’ and viewers’ opinions and perceptions of skincare products on the TikTok platform, specifically focusing on the local brand Camille Beauty. This dataset includes opinions, perceptions, reviews, and sentiments. It is stored in Excel format for text analysis, sentiment analysis, and social media marketing research. The dataset aims to provide insights and an overview of consumer behavior and public perception of the local skincare brand Camille Beauty on the TikTok digital platform.

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.

Dataset

This dataset was created by Sharipov Ibrokhim

Contents

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!

Need TikTok data that matches your research or business case? DataOx collects a custom TikTok dataset around the videos, creators, hashtags, comments, and engagement signals that matter to your use case.

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.

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 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 Reposts & Authors Dataset

This dataset contains archived TikTok reposts and user/author metadata scraped continuously via public TikTok API endpoints. It is split into two Parquet files for easy relational querying.

  📄 Dataset Structure

The dataset consists of two Parquet files:

  1. videos.parquet

Contains metadata for individual reposted TikTok videos.

Column Type Description

id String Unique TikTok video ID (Primary Key)

desc… See the full description on the dataset page: https://huggingface.co/datasets/EinzzCookie/TikTok-Video-User-Data.

[Region] Trending TikTok Videos – Verified Users

Dataset name: EinzzCookie/[region]-trending-tiktok-videos-verified-users-tiktok This dataset contains metadata of currently trending TikTok videos posted by verified accounts in the [Region] region.

  Source

Collected by EinzzCookie / TikTrackTelegram: @einzzcookie If you use this data, please credit the original source:https://einzzcookie.org/

  License

MIT

  Contents

The dataset typically… See the full description on the dataset page: https://huggingface.co/datasets/EinzzCookie/germany-trending-tiktok-videos-verified-users-tiktok.

🚀TikTok Shop Viral Video Sales, Attribution & CAC Analytics Dataset

📊 100,000 Transactions • 180+ Features • Creator Economics • Multi-Touch Attribution • CAC Optimization Traditional e-commerce analytics models are failing. In modern social commerce ecosystems like TikTok Shop, virality, creator authority, and micro-retention curves dictate revenue—not standard search traffic.

This dataset provides a production-grade analytical environment containing 100,000 granular observations and 180+ features. It bridges the gap between unstructured social media video engagement (hooks, rewatches, drop-offs) and enterprise financial performance (ROAS, CPA, Net Profit Margins, Multi-Touch Attribution).

💡 Why This Dataset Beats Standard Datasets End-to-End Customer Path: Tracks the complete journey from video impression and 3-second hook to product conversion and return risk.

Modern Social Commerce Vectors: Includes influencer tiering, affiliate tracking, and viral video hook dynamics that traditional retail datasets ignore.

Advanced Financial Metrics: Measures true net margins after creator commissions, platform fees, shipping costs, and customer acquisition expenses.

Multi-Touch Attribution Engine: Features First-Touch, Last-Touch, Linear, Position-Based, and Data-Driven revenue attribution models.

🧬 Dataset Schema & Feature Vectors (180+ Features) The data is structured into 6 interconnected analytical vectors:

1. 🎬 Video Performance & Content Hook Dynamics Video runtime, unique impressions, likes, shares, saves, retention curves at 3s and 10s, exact drop-off second, rewatch ratio, viral score, and hook clarity ratings.

2. 👤 Creator & Affiliate Intelligence Creator tier (Micro, Mid, Mega), follower count, engagement velocity, historical conversion authority, affiliate commission tier, and influencer ROI impact.

3. 💰 Financials & Unit Economics Gross revenue, net profit margin, Cost Per Acquisition (CPA), Customer Acquisition Cost (CAC), Return on Ad Spend (ROAS), platform fees, and marketing ROI.

4. 📈 Multi-Touch Attribution Models First-click revenue, last-click revenue, linear attribution, time-decay attribution, position-based model, and machine learning attribution confidence scores.

5. 🛒 Funnel & Traffic Analytics Product page clicks, add-to-cart rate, checkout abandonment rate, profile visits, traffic origin, and scroll depth.

6. 📦 Operations, Logistics & Profitability Shipping duration, delivery failure rate, return reason codes, processing cost, refund impact, and net contribution margin.

🎯 Machine Learning & Predictive Modeling Targets Use this dataset to build models targeting real-world business challenges:

Is_Viral (Binary Classification): Predict whether a video will achieve viral reach based on early 3-second hook metrics.

Net_Profit_Margin (Regression): Predict true profitability after subtracting creator commissions, return rates, and CAC.

Attribution_Model_Winner (Multi-Class Classification): Classify which attribution model best reflects true conversion impact based on customer path complexity.

Customer_Return_Probability (Predictive Modeling): Predict item return risk using product category, video claims, and shipping delays.

🚀 Quick-Start Analysis Snippet (Python)

import pandas as pd import numpy as np

Load dataset

df = pd.read_csv("tiktok_shop_viral_analytics_100k.csv")

1. Calculate Virality vs. Net Profitability Ratio

df['CAC_Efficiency'] = df['Net_Revenue'] / (df['CAC'] + 1e-5)

2. Compare ROAS across Creator Tiers

creator_perf = df.groupby('Creator_Tier')[['ROAS', 'Net_Profit_Margin', 'CAC']].mean() print("=== Creator Economics Overview ===") print(creator_perf)

3. Attribution Discrepancy Index

df['Attribution_Delta'] = df['Data_Driven_Revenue'] - df['Last_Click_Revenue'] print(" === Revenue Misattributed by Last-Click Model ===") print(df['Attribution_Delta'].describe())

🛠️ Recommended Portfolio Projects Project 1: Executive Creator Economics Dashboard (Power BI / Tableau) Visualize ROAS vs. Creator Commission rates across 100K transactions.

Project 2: Multi-Touch Attribution Engine (Python / SQL) Compare First-Touch vs. Data-Driven Attribution to reallocate marketing spend.

Project 3: Viral Hook & Drop-off Predictor (XGBoost / LightGBM) Predict video conversion failure using early 3-second viewer retention signals.

📌 Community Engagement & License License: CC0: Public Domain (Free for personal, academic, and commercial portfolio use).

Support: If you find this dataset valuable for your research, portfolio, or machine learning experiments, please ⭐ UPVOTE to support future dataset releases!

Showcase:Feel free to share your EDA notebooks and dashboard links in the Code and Discussion tabs!

TikTok videos and users by keyword or hashtag, extracted from public pages with the public Apify actor tiktok-search-scraper. Free public sample of 60 rows in JSON and CSV; full extraction is run on demand or on a schedule with your filters. Personal-data fields are not published.

In a context where there is permanent electoral campaigning, an increasing number of political communication experts are trying to unravel the resources used by government officials and their parties to influence TikTok users. From a broad perspective, the subject matter is not new, but it is topical; nonetheless, this research discloses a gap in the literature by amalgamating the recognition of idiosyncratic attributes of the feminisation of political discourse on TikTok with the analysis of the reactions (text and emojis) that the audiovisual content imbued by this trend elicits in users. The purpose is to ascertain whether the inclusive tone of the feminised rhetorical style can be extrapolated to TikTok and, if so, whether its particular characteristics mitigate expressions of incivility. To do so, the initial content posted (first seven months) on TikTok by the Spanish political platform Sumar with its leader, Yolanda Díaz, featuring prominently in most of the videos, were selected for scrutiny. A mixed methodology analysis of audiovisual content and comments showed that the anti-polarisation rhetoric and storytelling contributed to neutralising the extreme forms of flaming, although Sumar did not use a strategy tailor-made to suit TikTok.

The dataset represents the Tiktok user behavior using the platform that consist of Motivation, Platform, Product, and Host .

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.

Dataset collected for the study "Between Influence and Disinformation: Personal Branding and Responsible Communication of Influencers on TikTok." It contains coded data from 241 TikTok videos published by ten leading Spanish influencers between September and December 2025. Variables include engagement metrics, thematic classification, narrative tone, disinformation indicators, and commercial transparency markers.