Social Graph Tracking

Track follows, followers, mutuals, and interaction counts on ATProtocol.

When to Use

• Tracking engagement and relationship building

• Analyzing network connections

• Monitoring follower growth

• Identifying high-value interactions

Commands

Update graph with current data

uv run python -m tools.social update

Show social graph summary

uv run python -m tools.social show

Look up specific person

uv run python -m tools.social who <handle>

Data Structure

The social graph tracks:

{ "nodes": { "handle.bsky.social": { "did": "did:plc:xxx", "display_name": "Name", "first_seen": "2026-01-28T...", "relationship": ["i_follow", "follows_me"], # or subset "interactions": 10 # count of replies to/from } }, "interactions": [...], # recent interaction log "updated": "2026-01-28T..." }

Relationship Categories

Category Meaning

Mutuals Both follow each other

I follow You follow them, they don't follow back

Follow me They follow you, you don't follow back

Implementation

Core Functions

async def get_my_follows() -> list: """Get accounts I follow via app.bsky.graph.getFollows"""

async def get_my_followers() -> list: """Get accounts following me via app.bsky.graph.getFollowers"""

async def get_recent_interactions() -> list: """Analyze my posts to count reply interactions"""

Tracking Interactions

Interactions are counted by analyzing your posts:

• Each reply you make to someone increments their interaction count

• Sorted by interaction count to identify most engaged relationships

Usage Patterns

Daily Update

At start of session, refresh the graph

uv run python -m tools.social update

Identify Engagement Targets

See who you interact with most

uv run python -m tools.social show

Output:

Mutuals (8):

jowynter.bsky.social (10 interactions)

cameron.stream (5 interactions)

...

Research Before Engaging

Before replying to someone, check relationship

uv run python -m tools.social who someone.bsky.social

Storage

Data stored in data/social_graph.json

• JSON format for easy inspection and version control.

Integration with Experiments

Combine with metrics tracking to measure:

• Follower growth over time

• Correlation between engagement and growth

• Network expansion patterns

See references/social.py for full implementation.