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---
license: cc-by-4.0
pretty_name: "Farcaster Open Social Dataset"
tags:
- social-media
- farcaster
- farcaster-threads
- tabular
- parquet
- datasets
language: []
task_categories:
- text-retrieval
---
# Farcaster Threads Dataset
## Overview
This dataset contains high-quality thread data from Farcaster's entire history, featuring 512-dimensional embeddings generated using VoyageAI (float32) on formatted thread text. The dataset includes comprehensive thread metadata, engagement metrics, and vector embeddings suitable for semantic search, recommendation systems, and content analysis.
## Dataset Details
- **Total Records**: ~20,182,407 threads
- **Data Cutoff**: 2025-08-02 02:20:49.000 +0800 (no threads newer than this date)
- **Quality Filter**: Non-spam content only (spam label = 2), low-effort replies and threads removed.
- **Embedding Model**: VoyageAI 512-dimensional float32 vectors
- **Repository**: [shoni/farcaster](https://huggingface.co/datasets/shoni/farcaster)
- **Data Location**: `/threads` folder
## Schema
| Column | Type | Description |
|--------|------|-------------|
| `hash` | bytes | Unique thread identifier (primary key) |
| `fids` | list[int] | FIDs of reply authors, ordered by reaction count (most reacted first) |
| `reactions` | int | Total reaction count from non-spam users |
| `author_fid` | int | FID of the original thread author |
| `timestamp` | timestamp | Thread creation date |
| `claimed_at` | timestamp | When thread was claimed by processing worker |
| `blob` | string | Formatted thread text including replies and author information |
| `blob_embedding` | list[float32] | 512-dimensional VoyageAI embeddings of the blob text |
| `blob_timestamp` | timestamp | Timestamp of when the blob text was generated |
| `blob_embedding_binary` | bytes | Binary representation of the embeddings (512 bits) |
## Data Quality
- **Spam Filtering**: Only includes threads with spam label = 2 (verified non-spam)
- **Engagement Metrics**: Reaction counts filtered to exclude spam users
- **Historical Coverage**: Complete Farcaster thread history up to cutoff date
- **Reply Ordering**: Reply authors (`fids`) sorted by engagement for relevance
## Use Cases
- Semantic search over Farcaster content
- Thread recommendation systems
- Content similarity analysis
- Social network analysis
- Engagement prediction modeling
- Community detection and analysis
## Loading the Dataset
```python
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("shoni/farcaster", data_dir="threads")
# Access embeddings
embeddings = dataset['train']['blob_embedding']
# Access formatted thread text
threads = dataset['train']['blob']
```
## Citation
If you use this dataset in your research, please cite:
```
@dataset{farcaster_open_social_dataset_2025,
title={Farcaster Open Social Dataset},
author={shoni},
year={2025},
url={https://huggingface.co/datasets/shoni/farcaster}
}
```
## License
CC-BY-4.0
## Example Thread
Note: The actual `blob_embedding` content in the dataset uses private formatting techniques that slightly differ from the displayed blob text in the dataset. The displayed blob text is a human-readable format, replies are ordered from most to least popular (as whole branches):
```
@keremgurel: Beta launch is set for April 24th - exactly 3 months after the project kickoff. We’re building the first truly intuitive no-code website builder powered by blockchain, on @base https://imagedelivery.net/BXluQx4ige9GuW0Ia56BHw/5a93839e-f6be-4c04-b66a-4c2783328600/original https://stream.warpcast.com/v1/video/0195eca0-eccd-3042-b676-2f1bbd179695.m3u8
~1: @compusophy: cool!! though no need to use the word first here
~2: @keremgurel: Thanks! Why so? To my knowledge there aren’t any other onchain website builders out there
~1: @damag.eth: where can i sign up 👀
~2: @keremgurel: https://onchainsite.xyz https://onchainsite.xyz/
```
## Repository
[https://huggingface.co/datasets/shoni/farcaster](https://huggingface.co/datasets/shoni/farcaster)
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