Datasets:
metadata
license: cc-by-nc-sa-4.0
language:
- en
- tr
- es
- pt
- de
- fr
- ja
- it
- nl
- pl
- ru
- ko
- zh
- ar
- hi
task_categories:
- text-classification
- text-generation
- fill-mask
tags:
- social-media
- multilingual
- bluesky
- nlp
- sentiment-analysis
- text-classification
- language-modeling
- large-scale
- text-data
- posts
- microblog
- jsonl
- firehose
pretty_name: Bluesky 10M Multilingual Posts (15 Languages)
size_categories:
- 10M<n<100M
Dataset Card: Bluesky 10M Multilingual
π Overview
- Total Posts: 10,099,990
- Languages: 15 (en, tr, es, pt, de, fr, ja, it, nl, pl, ru, ko, zh, ar, hi)
- Collection Period: August 9-12, 2026
- Source: Bluesky Jetstream API (public firehose)
- Format: JSONL
- Size: ~3 GB
π Language Distribution
| Language | Code | Posts | % |
|---|---|---|---|
| English | en | 6,843,995 | 67.8% |
| Japanese | ja | 1,547,179 | 15.3% |
| German | de | 373,626 | 3.7% |
| Portuguese | pt | 331,093 | 3.3% |
| Spanish | es | 325,865 | 3.2% |
| French | fr | 206,852 | 2.0% |
| Korean | ko | 171,704 | 1.7% |
| Dutch | nl | 90,198 | 0.9% |
| Turkish | tr | 59,949 | 0.6% |
| Italian | it | 45,348 | 0.4% |
| Russian | ru | 27,892 | 0.3% |
| Chinese | zh | 26,695 | 0.3% |
| Polish | pl | 24,793 | 0.2% |
| Arabic | ar | 24,451 | 0.2% |
| Hindi | hi | 360 | 0.0% |
Distribution reflects natural Bluesky demographics.
π Data Fields
| Field | Type | Description |
|---|---|---|
did |
string | Decentralized user identifier |
rkey |
string | Record key (unique post ID) |
text |
string | Post content |
lang |
string | Primary language code |
created_at |
string | Post timestamp (ISO 8601) |
collected_at |
string | Collection timestamp |
is_reply |
bool | Whether post is a reply (optional) |
π» Usage
from datasets import load_dataset
# Load dataset
ds = load_dataset("itsmebatuhan/bluesky-10m-posts-15-languages", split="train")
# Access data
print(ds[0])
print(ds["lang"].value_counts())
Streaming (for large datasets)
ds = load_dataset("itsmebatuhan/bluesky-10m-posts-15-languages", streaming=True)
for sample in ds["train"]:
print(sample["text"])
break
π Citation
@dataset{bluesky_10m_multilingual_2026,
title = {Bluesky 10M Multilingual Posts (15 Languages)},
author = {itsmebatuhan},
year = {2026},
url = {https://huggingface.co/datasets/itsmebatuhan/bluesky-10m-posts-15-languages}
}