While I couldn’t find the exact criteria used for this specific table, Here’s a summary of my findings:
- Low Volume and Low Transaction Wallets:
- Wallets with low trading volumes and few transactions, particularly those with balances close to zero, are clear indicators of bot activity.
- Snapshots Comparison:
- When comparing two snapshots of the table, there’s an overall increase in the total number of detected bots. However, some wallets that were previously labeled as bots are no longer flagged in subsequent snapshots, indicating that the principle of “once a bot, always a bot” does not apply. This suggests that some wallets may change behavior or get cleared from bot detection criteria over time.
also these are the general patterns for bot detection:
- Trade Patterns: Identifying unusual or repetitive trading patterns that may indicate bot activity.
- Transaction Frequency: High-frequency transactions that are typical of automated bots.
- Order Book Analysis: Monitoring changes in the order book that suggest bot interference.
- Account Behavior: Tracking accounts that exhibit bot-like behavior, such as rapid trades or large volume trades.
Here’s how you can query, no need to click “Run”
