Note

I've removed the data from this dataset since there was a lot of community pushback about its creation/uploading. I will leave the dataset repository up to allow room for discussion of how datasets can be used to help improve Bluesky and allow people to build the tools they need to build their own open models and approaches to creating feeds that work for their needs. Please feel free to continue to leave feedback in the discussions here.

Dataset Card for 1 Million Bluesky Posts

This dataset contains 1 million public posts collected from Bluesky Social's firehose API, intended for machine learning research and experimentation with social media data.

The with-language-predictions config contains the same data as the default config but with language predictions added using the glotlid model.

Dataset Details

Dataset Description

This dataset consists of 1 million public posts from Bluesky Social, collected through the platform's firehose API. Each post contains text content, metadata, and information about media attachments and reply relationships.

Curated by: Daniel van Strien
Language(s) (NLP): Multiple (primarily English)
License: Dataset usage is subject to Bluesky's Terms of Service

Dataset Sources

Source: Bluesky Social firehose API
Collection Method: Python script (get_data.py) using the atproto library to connect to the firehose API and collect posts

Uses

Direct Use

This dataset could be used for:

Training and testing language models on social media content
Analyzing social media posting patterns
Studying conversation structures and reply networks
Research on social media content moderation
Natural language processing tasks using social media datas

Out-of-Scope Use

This dataset should not be used for:

Building automated posting systems for Bluesky
Creating fake or impersonated content
Extracting personal information about users
Any purpose that violates Bluesky's Terms of Service

Dataset Structure

The dataset is available in two configurations:

Default Configuration

Contains the following fields for each post:

text: The main content of the post
created_at: Timestamp of post creation
author: The Bluesky handle of the post author
uri: Unique identifier for the post
has_images: Boolean indicating if the post contains images
reply_to: URI of the parent post if this is a reply (null otherwise)

With Language Predictions Configuration

Contains all fields from the default configuration plus:

predicted_language: The predicted language code (e.g., eng_Latn, deu_Latn)
language_confidence: Confidence score for the language prediction (0-1)

Language predictions were added using the glotlid model via fasttext, with the process documented in predict_language.ipynb.

Dataset Creation

Curation Rationale

This dataset was created to provide researchers and developers with a large sample of Bluesky posts for machine learning experimentation and social media analysis.

Source Data

Data Collection and Processing

Posts were collected using a Python script that connects to Bluesky's firehose API using the atproto library. The script:

Processes the real-time feed of public posts
Extracts relevant fields from each post
Saves posts in batches of 100,000 to JSONL files
Includes basic metadata and structural information about each post

Who are the source data producers?

The data comes from public posts made by Bluesky Social users. These users represent a diverse group of individuals and organizations who have chosen to share content publicly on the platform.

Personal and Sensitive Information

The dataset contains public posts and their associated public metadata. While all data is publicly available through Bluesky's API, users should:

Respect user privacy and platform Terms of Service
Not attempt to de-anonymize or aggregate user information
Use the data responsibly and ethically

Bias, Risks, and Limitations

The dataset represents a snapshot in time and may not reflect current platform usage
Content may be biased towards more active users or specific time periods
Posts are not filtered for content or quality
The dataset may contain biases present in the Bluesky user base
Language distribution may not be representative of all Bluesky users, especially since the posts where collected over a brief period of time when some timezones were asleep
Language predictions are automated and may contain errors, especially for short texts or mixed-language content
The language detection model may have its own biases and limitations in detecting certain languages or scripts

Datasets:

bluesky-community
/

one-million-bluesky-posts

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