metadata
license: cc-by-nc-4.0
task_categories:
- text-classification
- feature-extraction
language:
- zh
size_categories:
- 1M<n<10M
Douyin Posts Dataset
A dataset of 1,133,545 unique posts from Douyin (Chinese TikTok), collected via snowball sampling of related videos.
Dataset Description
This dataset contains metadata from Douyin short videos, collected by crawling related video recommendations. Starting from seed videos matching specific keywords, the crawler iteratively fetched related videos to build a diverse sample of the platform's content.
Collection Method
- Snowball sampling: Starting from keyword-matched seed videos, related videos were iteratively crawled
- Deduplication: All posts are deduplicated by
aweme_id(unique video identifier) - Partitioning: Data is partitioned by the first 4 digits of
aweme_idfor efficient access
Dataset Structure
The dataset contains 187 columns. Key fields include:
Core Fields
| Field | Type | Description |
|---|---|---|
aweme_id |
string | Unique video identifier |
desc |
string | Video description/caption |
caption |
string | Short caption |
create_time |
int64 | Unix timestamp of video creation |
duration |
int64 | Video duration in milliseconds |
region |
string | Geographic region code |
Engagement Statistics (statistics struct)
| Field | Description |
|---|---|
digg_count |
Number of likes |
comment_count |
Number of comments |
share_count |
Number of shares |
play_count |
Number of views |
collect_count |
Number of saves/bookmarks |
Author Information (author struct)
| Field | Description |
|---|---|
uid |
Author user ID |
nickname |
Display name |
sec_uid |
Secondary user ID |
signature |
Author bio |
follower_status |
Follower relationship status |
Content Metadata
| Field | Type | Description |
|---|---|---|
cha_list |
list | Hashtag/challenge information |
text_extra |
list | Extracted hashtags, mentions, and links |
music |
struct | Audio/music metadata |
video |
struct | Video file metadata (URLs, dimensions, formats) |
poi_info |
struct | Location/point of interest data |
Usage
import polars as pl
from huggingface_hub import hf_hub_download
from pathlib import Path
# Download a single partition
file_path = hf_hub_download(
repo_id="bendavidsteel/douyin",
filename="data/partition_7500.parquet.zstd",
repo_type="dataset"
)
df = pl.read_parquet(file_path)
# Or load all partitions
from huggingface_hub import snapshot_download
local_dir = snapshot_download(
repo_id="bendavidsteel/douyin",
repo_type="dataset",
allow_patterns="data/*.parquet.zstd"
)
df = pl.read_parquet(Path(local_dir) / "data" / "*.parquet.zstd")
File Structure
data/
├── partition_7035.parquet.zstd
├── partition_7040.parquet.zstd
├── ...
└── partition_7551.parquet.zstd
111 partition files, partitioned by the first 4 digits of aweme_id.
Limitations
- Metadata only - does not include actual video/image content
- Point-in-time snapshot - engagement statistics reflect collection time
- Related video sampling may introduce biases toward popular/recommended content
License
CC-BY-NC-4.0 (Creative Commons Attribution-NonCommercial 4.0)