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    Ethereum Network Integrity: Quality User Behavior & Capital Flow Analysis

    This dashboard analyzes key on-chain activity on the Ethereum network over the past 90 days, focusing specifically on high-quality user behavior. Metrics are filtered using Flipside’s Quality Score (≥ 4), offering insights into the organic health, fee contribution, and transaction integrity of the network.

    Methodology

    • Data Source: datascience_public.ethereum.chain_stats

    • Date Range: CURRENT_DATE - INTERVAL '90 days'

    • Filtering: High-quality users = Flipside Score ≥ 4

    • Metrics Tracked:

      • Users: Active, Quality Active

      • Transactions: Count, Quality Count

      • Fees: ETH & USD (Total & Quality)

      • Transfers: Volume (USD, Total vs. Quality)

      • TVL

      • Correlation between all major metrics

    User Breakdown and Participation
    Transaction Analysis

    1. Daily Active vs. Quality Active Users

    • Description: Visualizes daily total active users alongside the subset passing quality thresholds.

    • Insight: Helps assess the share and stability of high-quality participation in Ethereum's on-chain activity.

    2. Daily Quality User Percentage

    • Description: Shows the percentage of active users that meet quality criteria each day.

    • Insight: Measures behavioral integrity among users; significant dips may imply bot surges or short-term inorganic activity.

    3. Daily Transactions vs. Quality Transactions

    • Description: Compares overall transaction volume to transactions from high-quality users.

    • Insight: Allows us to monitor how much daily activity is driven by organic, quality users.

    4. Daily Quality Transaction Percentage

    • Description: Percentage of all transactions considered high-quality.

    • Insight: Useful for identifying shifts in organic engagement patterns. Sharp drops may indicate inorganic or speculative spikes.

    Fee Contribution by Quality Users

    5. Daily Total vs. Quality Fees (USD)

    • Description: Total transaction fees vs. those contributed by quality users (in USD).

    • Insight: Shows financial participation integrity—i.e., are valuable network contributors also high quality?

    6. Daily Quality Fee Percentage

    • Description: Percentage of total fees paid by high-quality users.

    • Insight: Declines may signal gamified/spammy fee-driven activity from low-quality actors.

    Correlation Insights

    7. Daily Correlation: Quality User % vs. Quality Fee %

    • Description: Correlation between the share of quality users and the share of fees they contribute.

    • Insight:

      • Coefficient: -0.007

      • Interpretation: Very weak negative correlation. This suggests that increases in quality user count don’t strongly predict increases in their fee share.

    8. Quality Users’ Fee Sensitivity Over Time

    • Description: Compares average fee per quality transaction (in ETH) vs. total daily fees.

    • Insight: Evaluates if high-quality users adjust behavior when network fees rise.

      • High correlation (0.8): Indicates high-quality users are sensitive to network conditions and potentially adjust engagement accordingly.

    Transfer Activity

    9. Daily Total vs. Quality Transfer Volume (USD)

    • Description: Compares total token transfer volume to that initiated by high-quality users (in USD).

    • Insight: Gauges the role of quality users in capital movement on Ethereum.

    10. Daily Quality Transfer Volume Ratio

    • Description: Shows the share of transfer volume attributable to quality users.

    • Insight:

      • Average Ratio: 0.08

      • Indicates that only ~8% of daily transfer volume comes from high-quality actors—potentially revealing heavy speculative/inorganic capital flow.

    TVL Correlation Analysis

    11. Correlation Between TVL and Key Quality Metrics

    • Description: Displays Pearson correlations between TVL (USD) and:

      • Quality Transactions: ~0.47

      • Quality Fees (USD): ~0.53

      • Active Quality Users: ~0.61

    Interpretation:

    • Moderate Positive Correlation in all metrics suggests:

      • When more value is locked in the network, there tends to be more high-quality activity.

      • Especially stronger for active quality users, implying TVL may attract more organic participation.

    Disclaimer: Flipside AI is here to help but it can make mistakes. Always review outputs and use the upvote/downvote buttons to help us improve. This content is not financial advice.