Fake Follower Risk Check: vet a creator with measured detection criteria
You do not need a paid tool to check for fake followers — you need to know which four signals to read. This checklist uses the same criteria as the anomaly detection we run across 97,000+ accounts, where roughly 7% get flagged as suspected inflated — with big differences by platform (table below).
Measured suspected-inflated rate by platform
Results of the anomaly detection we run across our index — telling you where vetting must be budgeted as a real cost:
| Platform | Suspected inflated |
| Threads | 15.5% |
| TikTok | 12.2% |
| Twitch | 10.9% |
| X (Twitter) | 10.3% |
| Douyin | 7.3% |
| 6.9% | |
| Xiaohongshu | 3.8% |
| 1.6% | |
| YouTube | 1.5% |
| 1.4% |
Full analysis (follower-tier breakdown + methodology): the fake-follower study. In Koinon Link creator data, suspected-inflated accounts are quarantined out of default results automatically.
Cite this page
Koinon Link (2026). Fake Follower Risk Check: vet a creator with measured detection criteria. Data as of 2026-10-22. https://koinonlink.com/tools/fake-follower-risk-checkStatistics are licensed CC BY 4.0: attribute “Koinon Link” with a link to this page. Figures recompute daily — include the data date when citing. Machine-readable version: /tools/fake-follower-risk-check.json
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