@teolipeng14
On-chain data analysis helps project teams identify genuine users by examining blockchain transaction patterns and behaviors. First, they analyze wallet activity, focusing on consistent transaction history, frequency, and volume to distinguish active users from bots or inactive accounts. Second, they track token interactions, such as staking, trading, or governance participation, to confirm user engagement. Third, cross-referencing wallet addresses with off-chain data, like social media activity or KYC, ensures authenticity. Additionally, anomaly detection algorithms flag suspicious activities, such as wash trading or Sybil attacks. By combining metrics like gas fees, contract interactions, and network diversity, projects can effectively filter out fake accounts and prioritize real users for fairer, more secure ecosystems.
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