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--- |
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license: cc-by-4.0 |
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pretty_name: "Farcaster Open Social Dataset" |
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tags: |
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- social-media |
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- farcaster |
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- farcaster-threads |
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- tabular |
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- parquet |
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- datasets |
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language: [] |
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task_categories: |
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- text-retrieval |
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--- |
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# Farcaster Threads Dataset |
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## Overview |
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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. |
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## Dataset Details |
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- **Total Records**: ~20,182,407 threads |
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- **Data Cutoff**: 2025-08-02 02:20:49.000 +0800 (no threads newer than this date) |
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- **Quality Filter**: Non-spam content only (spam label = 2), low-effort replies and threads removed. |
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- **Embedding Model**: VoyageAI 512-dimensional float32 vectors |
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- **Repository**: [shoni/farcaster](https://huggingface.co/datasets/shoni/farcaster) |
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- **Data Location**: `/threads` folder |
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## Schema |
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| Column | Type | Description | |
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|--------|------|-------------| |
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| `hash` | bytes | Unique thread identifier (primary key) | |
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| `fids` | list[int] | FIDs of reply authors, ordered by reaction count (most reacted first) | |
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| `reactions` | int | Total reaction count from non-spam users | |
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| `author_fid` | int | FID of the original thread author | |
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| `timestamp` | timestamp | Thread creation date | |
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| `claimed_at` | timestamp | When thread was claimed by processing worker | |
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| `blob` | string | Formatted thread text including replies and author information | |
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| `blob_embedding` | list[float32] | 512-dimensional VoyageAI embeddings of the blob text | |
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| `blob_timestamp` | timestamp | Timestamp of when the blob text was generated | |
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| `blob_embedding_binary` | bytes | Binary representation of the embeddings (512 bits) | |
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## Data Quality |
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- **Spam Filtering**: Only includes threads with spam label = 2 (verified non-spam) |
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- **Engagement Metrics**: Reaction counts filtered to exclude spam users |
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- **Historical Coverage**: Complete Farcaster thread history up to cutoff date |
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- **Reply Ordering**: Reply authors (`fids`) sorted by engagement for relevance |
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## Use Cases |
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- Semantic search over Farcaster content |
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- Thread recommendation systems |
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- Content similarity analysis |
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- Social network analysis |
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- Engagement prediction modeling |
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- Community detection and analysis |
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## Loading the Dataset |
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```python |
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from datasets import load_dataset |
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# Load the dataset |
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dataset = load_dataset("shoni/farcaster", data_dir="threads") |
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# Access embeddings |
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embeddings = dataset['train']['blob_embedding'] |
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# Access formatted thread text |
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threads = dataset['train']['blob'] |
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``` |
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## Citation |
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If you use this dataset in your research, please cite: |
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``` |
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@dataset{farcaster_open_social_dataset_2025, |
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title={Farcaster Open Social Dataset}, |
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author={shoni}, |
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year={2025}, |
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url={https://huggingface.co/datasets/shoni/farcaster} |
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} |
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``` |
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## License |
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CC-BY-4.0 |
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## Example Thread |
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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): |
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``` |
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``` |
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## Repository |
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[https://huggingface.co/datasets/shoni/farcaster](https://huggingface.co/datasets/shoni/farcaster) |
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