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README.md

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+---
+license: mit
+pretty_name: Farcaster Links
+---
+
+# Farcaster Public Links Dataset
+
+This dataset contains public follow relationships from the Farcaster social protocol that have not been deleted by their authors. The dataset includes comprehensive metadata for each link, allowing for detailed analysis of the social graph in the Farcaster ecosystem.
+
+## Dataset Description
+
+The dataset contains the following fields for each active link:
+- `Fid`: The Farcaster ID of the user who created the link
+- `MessageType`: Type of message (all are 'LinkAdd' as deleted links are excluded)
+- `Timestamp`: Seconds since the Farcaster Epoch (January 1, 2021 00:00:00 UTC)
+- `LinkType`: The type of link (primarily 'follow')
+- `TargetFid`: The Farcaster ID of the user being followed
+
+## Timestamp Format
+
+Timestamps in this dataset use the Farcaster epoch (seconds since January 1, 2021 00:00:00 UTC).
+
+To convert to a standard Unix timestamp:
+1. Add 1609459200 (Unix timestamp for January 1, 2021 00:00:00 UTC) 
+2. The result will be a standard Unix timestamp
+
+Example in Python:
+```python
+# Convert Farcaster timestamp to Unix timestamp
+unix_timestamp = farcaster_timestamp + 1609459200
+
+# Convert to datetime
+from datetime import datetime
+dt = datetime.fromtimestamp(unix_timestamp)
+```
+
+## Key Statistics
+- Format: Single Parquet file
+- Link types: Primarily 'follow' relationships
+- Dataset includes all non-deleted links from the Farcaster network as of March 21, 2025
+
+## Intended Uses
+
+This dataset can be useful for:
+- Analyzing the social graph of the Farcaster network
+- Identifying influential users through follower analysis
+- Studying follow/following patterns and community structures
+- Tracking growth of the network over time
+- Building recommendation algorithms based on social connections
+- Researching information diffusion patterns
+- Creating social network visualizations
+- Analyzing community formation and evolution
+
+## Example Queries
+
+Using Python and pandas:
+```python
+import pandas as pd
+import numpy as np
+from datetime import datetime
+
+# Load the dataset
+df = pd.read_parquet('farcaster_links.parquet')
+
+# Convert timestamps to datetime
+df['datetime'] = df['Timestamp'].astype(int).apply(
+    lambda x: datetime.fromtimestamp(x + 1609459200)
+)
+
+# Count followers for each user
+follower_counts = df.groupby('TargetFid').size().sort_values(ascending=False)
+
+# Top 20 most followed accounts
+top_followed = follower_counts.head(20)
+
+# Analyze follow trends over time
+monthly_follows = df.groupby(df['datetime'].dt.strftime('%Y-%m')).size()
+```
+
+Using DuckDB:
+```sql
+-- Count followers for each user
+SELECT 
+  TargetFid,
+  COUNT(*) AS follower_count
+FROM 'farcaster_links.parquet'
+GROUP BY TargetFid
+ORDER BY follower_count DESC
+LIMIT 20;
+
+-- Find users with most outgoing follows
+SELECT 
+  Fid,
+  COUNT(*) AS following_count
+FROM 'farcaster_links.parquet'
+GROUP BY Fid
+ORDER BY following_count DESC
+LIMIT 20;
+
+-- Analyze follow growth by day
+SELECT 
+  DATE_TRUNC('day', TIMESTAMP '2021-01-01 00:00:00' + (CAST(Timestamp AS BIGINT) * INTERVAL '1 second')) AS follow_date,
+  COUNT(*) AS daily_follow_count
+FROM 'farcaster_links.parquet'
+GROUP BY follow_date
+ORDER BY follow_date;
+```
+
+## Limitations
+- Does not include user profile information
+- Only includes LinkAdd relationships (not other link types)
+- Does not include the content of users' casts
+- Does not include information about user interactions
+
+## Ethics & Privacy
+- This dataset contains only public follow relationships that were publicly accessible on the Farcaster protocol
+- Deleted relationships have been excluded to respect user content choices
+- Personal information beyond public FIDs has been excluded
+- Users should respect Farcaster's terms of service when using this data
+- Researchers should be mindful of potential biases in social media datasets
+
+## License
+MIT License
+
+## Updates
+This dataset represents a snapshot of Farcaster follow relationships as of March 21, 2025. For live data, please refer to the Farcaster protocol directly or check for updated versions of this dataset.
+