Bot filtering is the set of techniques used to detect and exclude automated, non-human activity from campaign metrics and reward calculations. Common methods include traffic-source analysis, session-quality scoring, device and IP caps, and wallet-quality checks. The strength of a platform’s bot filtering directly determines how much of a reward pool reaches real participants.
Each method closes a different gap. Traffic-source analysis catches traffic arriving from known automation networks. Session-quality scoring separates a visitor who read something from one who bounced in under a second. Device and IP caps limit how much a single machine can earn regardless of how many accounts it drives. Wallet-quality checks weigh the on-chain history behind a participant.
Filtering is adversarial and permanent, not a feature that gets finished. Every reward pool is an incentive to defeat the filter, which is why platforms pair it with reputation signals and anomaly review rather than relying on any single check.
