lingbow/tiktok-video-engagement-1m

TikTok Creator and Video Engagement (1M)

This release contains 1,035,817 TikTok videos from 4,926 creators with daily engagement and follower statistics, covering videos posted from 2024-06-09 to 2025-03-20.

Github: https://github.com/lingbowzd/tiktok-creator-video-trend-data

Arxiv: coming soon...

Uses

This dataset supports research on TikTok creator behavior, content strategy, trend adoption, and audience engagement over time. Unlike random collections of TikTok videos, it is a longitudinal creator-level dataset that tracks creators’ posting behavior and follower growth over 9 months, with 30-day engagement trajectories for each video.

The dataset can be used for predictive modeling, time-series forecasting, and creator-level panel analysis. It is designed for researchers, students, and data practitioners working in computational social science, marketing, creator-economy research, business analytics, and data science.

Content

The dataset is organized as three linked Parquet tables.

Config	File	Unit of observation	Rows	Columns
videos	videos.parquet	one row per video	1,035,817	19
engagement_daily	engagement_daily.parquet	one row per video-date during days 0-30 after posting	27,169,858	10
creator_daily	creator_daily.parquet	one row per creator-date	937,484	7

videos.video_id links to engagement_daily.video_id, and videos.author_id links to creator_daily.author_id. Video hashtags and music identifiers can also be joined to the separate TikTok Trend Context release.

Video Metadata and Coverage

Statistic	Value
Videos	1,035,817
Unique creators in videos	4,926
Video posting window	2024-06-09 to 2025-03-20
Videos with is_english = 1	522,261
Videos with at least one attached hashtag	715,031
Total video-hashtag links	4,583,953
Videos with music ID	1,032,804
Duration mean, seconds	39.4
Duration p50 / p75 / p95, seconds	15.5 / 50.0 / 139.6

Engagement Statistics

The engagement table records cumulative counters observed on each date.

Statistic	Value
Video-day observations	27,169,858
Unique videos in engagement_daily	1,035,797
Engagement observation window	2024-06-09 to 2025-03-20
days_since_post range	0 to 30

Counter	p50	p75	p90	p95	p99
play_count	532	1,898	14,515	50,391	432,004
like_count	40	114	786	3,339	36,541
comment_count	2	9	31	79	549
share_count	0	3	22	97	1,755
collect_count	2	6	44	187	2,314

Creator Statistics

Statistic	Value
Creator-day observations	937,484
Unique creators in creator_daily	4,920
Creator observation window	2024-06-09 to 2025-03-28
Median follower count	6,981
75th percentile follower count	27,584
95th percentile follower count	404,173

Data Fields

videos

Column	Description
video_id	Video identifier.
author_id	Creator identifier used to link creator-level records.
create_time, create_date	Video creation timestamp and date.
duration	Video duration in seconds.
ratio	Video aspect/quality metadata as collected.
desc_language, is_english	Detected description language and English-language indicator.
desc, sticker_text	Publicly visible text fields associated with the video when available.
hashtags	List of {hashtag_id, hashtag_name} objects attached to the video.
created_by_ai, is_ads	Platform metadata when available.
music_selected_from, music_album, music_author, music_owner_id, music_id, music_title	Music metadata.

engagement_daily

Column	Description
video_id	Video identifier.
date	Observation date.
days_since_post	Days elapsed since the video was posted, from 0 to 30.
play_count, like_count, comment_count, share_count, collect_count, download_count, whatsapp_share_count	Cumulative engagement counters observed on that date.

creator_daily

Column	Description
author_id	Creator identifier.
date	Observation date.
follower_count, following_count, total_favorited, video_count	Creator account statistics observed on that date.
enterprise_verified	Enterprise verification indicator when available.

Load With Hugging Face Datasets

from datasets import load_dataset

videos = load_dataset("lingbow/tiktok-video-engagement-1m", "videos")["train"]
engagement = load_dataset("lingbow/tiktok-video-engagement-1m", "engagement_daily")["train"]
creators = load_dataset("lingbow/tiktok-video-engagement-1m", "creator_daily")["train"]

Load With Pandas

import pandas as pd

base = "hf://datasets/lingbow/tiktok-video-engagement-1m"

videos = pd.read_parquet(f"{base}/videos.parquet")
engagement = pd.read_parquet(f"{base}/engagement_daily.parquet")
creators = pd.read_parquet(f"{base}/creator_daily.parquet")

Join Tables

Use video_id to merge video metadata with daily engagement records, and use author_id plus date to merge creator-day statistics.

video_panel = engagement.merge(videos, on="video_id", how="left")

video_panel = video_panel.merge(
    creators,
    on=["author_id", "date"],
    how="left",
)

Limitations and Ethics

The release contains metadata and engagement records, not raw video files. Engagement counters are observational and reflect both audience behavior and platform recommendation/ranking dynamics. The dataset should not be treated as a representative sample of all TikTok videos or all TikTok creators.

This dataset is intended for academic and non-commercial research. Users should follow platform terms, applicable law, and institutional review requirements.

Citation

@dataset{tiktok_video_engagement_1m,
  title = {TikTok Creator and Video Engagement (1M)},
  author = {Lingbo Wang},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/lingbow/tiktok-video-engagement-1m}
}