Social graph export: followers, following and mutuals in three calls

Individual connection lists are snapshots; a social graph export — followers plus following on both sides of a relationship — is the dataset that answers real questions. This tutorial builds one for a cross-network workflow: an Instagram account and the Facebook page of the same brand.

What we export

Endpoint	Network	Edges
Followers	Instagram	audience → account
Following	Instagram	account → follows
Facebook followers	Facebook	audience → page
Facebook followings	Facebook	page → follows

Four paginated walks, one shared helper — every list is cursor-based, so the pattern is identical (see the followers export guide for the loop; Facebook uses after instead of max_id).

from getsocialapi import Client
from getsocialapi_facebook import FacebookAPI, Transport

ig = Client(api_key="gsa_live_...").instagram
fb = FacebookAPI(Transport(
    base_url="https://api.getsocialapi.com/fb",
    api_key="gsa_live_..."))

def ig_export(fn, uid):
    rows, cursor = [], None
    while True:
        page = fn(uid, count=50, max_id=cursor)
        rows += page["users"]
        cursor = page.get("next_max_id")
        if not cursor:
            return rows

ig_followers  = ig_export(ig.followers, ig_uid)
ig_following  = ig_export(ig.following, ig_uid)

Mutuals: the community core

f_ids = {u["pk"] for u in ig_followers}
g_ids = {u["pk"] for u in ig_following}
mutuals = f_ids & g_ids
print(f"followers={len(f_ids)}, following={len(g_ids)}, mutual={len(mutuals)}")

Mutuals are the strongest relationship signal both networks expose: each side opted into the other. Growth teams treat mutual-count trajectory as a leading engagement indicator — it moves before follower count does.

Ratio and asymmetry

ratio = len(f_ids) / max(len(g_ids), 1)
one_way = g_ids - f_ids   # follows them, they don't follow back

• ratio >> 1 — broadcast account (media, brand).
• ratio ≈ 1 with high mutuals — personal/community account.
• one_way dominated by spam-pattern profiles — audience quality debt.

Cross-network identity hints

Facebook pages and Instagram accounts of the same brand rarely share ids — but they share people. Sample usernames/normalized names from both follower lists and intersect: the overlap coefficient between the two audiences measures how separable the communities really are (marketing teams use it to decide whether to run one strategy or two).

Storage shape

One table beats clever schemas at collection time:

edges(source, target, network, edge_type, first_seen, last_seen)

Re-running the export updates last_seen; edges that disappear move to an archive table. Churn (edges with stale last_seen) is itself a dataset — audience decay per account.

Budget math

A brand with 50k Instagram followers + 3k following and a Facebook page with 20k followers is ~1 500 + 60 + ~1 300 + ~200 requests — about 3 100 calls, an hour of polite pacing, resumable via cursors at any point. The rate limits guide covers the retry loop.

Four walks, one table, every graph question — getsocialapi.com, first 100 calls free.

Build with GetSocialAPI

Explore Instagram API and Facebook API for capabilities, pricing and integration examples. Create an account to start with 100 free calls, or follow the quickstart.