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How to Map TikTok Creator Networks

Build follower-following network maps of TikTok creators to find collaboration clusters. Python implementation at $0.005/call.

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TikTok creator networks reveal who influences whom. Mapping follower-following connections helps brands find collaboration clusters, bridge creators connecting niches, and avoid sponsoring creators with redundant audiences. This tutorial uses Scavio's TikTok follower and following endpoints at $0.005/call.

Prerequisites

  • Python 3.8+
  • requests and networkx installed
  • A Scavio API key from scavio.dev
  • Seed TikTok creators

Walkthrough

Step 1: Fetch profile and following data

Pull who each creator follows.

Python
import os, requests

API_KEY = os.environ['SCAVIO_API_KEY']
H = {'Authorization': f'Bearer {API_KEY}', 'Content-Type': 'application/json'}

def get_profile(username):
    user = requests.post('https://api.scavio.dev/api/v1/tiktok/profile',
        headers=H, json={'username': username}).json()['data']['user']
    return {'username': user['unique_id'], 'sec_uid': user['sec_uid'],
            'followers': user['follower_count']}

def get_following(sec_uid, limit=30):
    following = []
    params = {'sec_user_id': sec_uid, 'count': 20}
    while len(following) < limit:
        resp = requests.post('https://api.scavio.dev/api/v1/tiktok/user/followings',
            headers=H, json=params).json()['data']
        following.extend([u['unique_id'] for u in resp.get('users', [])])
        if not resp.get('has_more'): break
        params['max_cursor'] = resp.get('max_cursor', 0)
    return following[:limit]

Step 2: Build the network graph

Create edges between creators.

Python
import networkx as nx

def build_network(seeds):
    G = nx.DiGraph()
    for username in seeds:
        profile = get_profile(username)
        G.add_node(username, followers=profile['followers'])
        following = get_following(profile['sec_uid'])
        for f in following: G.add_edge(username, f)
        print(f'  @{username}: {len(following)} following')
    mutual = [(u, v) for u, v in G.edges() if G.has_edge(v, u)]
    print(f'Network: {G.number_of_nodes()} nodes, {len(mutual)} mutual follows')
    return G

G = build_network(['creator1', 'creator2', 'creator3'])

Step 3: Find bridge creators

Identify connectors with high betweenness centrality.

Python
def find_bridges(G):
    undirected = G.to_undirected()
    centrality = nx.betweenness_centrality(undirected)
    top = sorted(centrality.items(), key=lambda x: x[1], reverse=True)[:5]
    print('Bridge creators:')
    for user, score in top:
        print(f'  @{user}: centrality={score:.3f}, followers={G.nodes[user].get("followers", "?")}')

find_bridges(G)

Step 4: Estimate cost

Calculate API cost for network mapping.

Python
def estimate_cost(seed_count, pages_per=2):
    calls = seed_count + seed_count * pages_per  # profile + following pages
    cost = calls * 0.005
    print(f'{seed_count} seeds: {calls} calls, ${cost:.2f}')

estimate_cost(5)
estimate_cost(20)

Python Example

Python
import os, requests
API_KEY = os.environ['SCAVIO_API_KEY']
H = {'Authorization': f'Bearer {API_KEY}', 'Content-Type': 'application/json'}

def get_following(username):
    user = requests.post('https://api.scavio.dev/api/v1/tiktok/profile',
        headers=H, json={'username': username}).json()['data']['user']
    resp = requests.post('https://api.scavio.dev/api/v1/tiktok/user/followings',
        headers=H, json={'sec_user_id': user['sec_uid'], 'count': 20}).json()
    return [u['unique_id'] for u in resp['data'].get('users', [])]

for c in ['creator1']: print(f'@{c} follows: {", ".join(get_following(c)[:5])}')

JavaScript Example

JavaScript
const API_KEY = process.env.SCAVIO_API_KEY;
const H = { Authorization: `Bearer ${API_KEY}`, 'Content-Type': 'application/json' };
async function getFollowing(username) {
  const p = await fetch('https://api.scavio.dev/api/v1/tiktok/profile', {
    method: 'POST', headers: H, body: JSON.stringify({ username })
  }).then(r => r.json());
  const r = await fetch('https://api.scavio.dev/api/v1/tiktok/user/followings', {
    method: 'POST', headers: H,
    body: JSON.stringify({ sec_user_id: p.data.user.sec_uid, count: 20 })
  }).then(r => r.json());
  return (r.data.users || []).map(u => u.unique_id);
}
getFollowing('creator1').then(f => console.log(f.slice(0, 5))).catch(console.error);

Expected Output

JSON
  @creator1: 28 following
  @creator2: 35 following
  @creator3: 22 following
Network: 45 nodes, 12 mutual follows

Bridge creators:
  @creator2: centrality=0.340, followers=85000

Related Tutorials

  • How to Get TikTok Profile Data via API
  • How to Build a TikTok Influencer Vetting Pipeline
  • How to Build a TikTok Audience Overlap Report

Frequently Asked Questions

Most developers complete this tutorial in 15 to 30 minutes. You will need a Scavio API key (free tier works) and a working Python or JavaScript environment.

Python 3.8+. requests and networkx installed. A Scavio API key from scavio.dev. Seed TikTok creators. A Scavio API key gives you 50 free credits on signup.

Yes. The free tier includes 50 credits on signup, which is more than enough to complete this tutorial and prototype a working solution.

Scavio has a native LangChain package (langchain-scavio), an MCP server, and a plain REST API that works with any HTTP client. This tutorial uses the raw REST API, but you can adapt to your framework of choice.

Related Resources

Best Of

Best TikTok Influencer Vetting APIs (2026)

Read more
Best Of

Best TikTok Creator Discovery API in 2026

Read more
Solution

Map TikTok Creator Networks via Follower Graph

Read more
Glossary

TikTok Creator Vetting API Pattern

Read more
Glossary

TikTok Creator Graph

Read more
Comparison

Manual TikTok Vetting vs API-Driven Creator Vetting

Read more

Start Building

Build follower-following network maps of TikTok creators to find collaboration clusters. Python implementation at $0.005/call.

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