Sybil Report on Gitcoin Grants Rounds 10

tags: gitcoin Reports

Updated by December 2021

Authors: Danilo Lessa Bernardineli

This doc reports how the Gitcoin Contributions Graph changes when it is modified so that users are excluded based on a list provided by the Sybil Detection Algorithm. Summary statistics and a estimate of the Fraud Tax is computed (as defined at https://hackmd.io/e2mZ9UT7QRGMh5tg6OCXfw).

Parameters

Algorithm Aggressiveness: 20%
Matching Pool: 700k USD

Algorithm Aggressiveness tunes how much sensitive / specific the flagging model should be. When it is set to 50%, then it will be optimized for accuracy, while closer values to 0% means that it will be optimized for minimizing false detection rate

Summary Statistics

Total Contributions (original): 320295
Total Contributions (modified): 320295

Matched Contributions (original): 320295
Matched Contributions (modified): 289417 (90.4% of original)

Total Contributors (original): 14203
Total Contributors (modified): 12933 (91.1% of original)

Median Contribution Count per User (original): 11.00
Median Contribution Count per User (modified): 11.00

Mean Count (original): 22.55
Mean Count (modified): 24.77 (109.8% of original)

Grant Statistics

Total Grant Funding (original): 700000.00
Total Grant Funding (modified): 700000.00

Mean Grant Funding (USDT, original): 772.63
Mean Grant Funding (USDT, modified): 776.91

Median Grant Funding (USDT, original): 0.48
Median Grant Funding (USDT, modified): 0.51

Grant count (original): 906
Grant count (modified): 901

Fraud tax

Max payout (USDT): 714394.79

Fraud Tax: 14,394.79 USD

Taxation Quotient: 2.05%

Notes from 2021-12-22

Samples = 94 (34 true)
Estimated Sybil Incidence: 36.2% (between 26.1% and 45.4% 95% CI)

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