Thanks for your response. I guess this could be cleared up if we knew how the squelching was done.
Maybe I missed that?
I see the following text:
After on-chain data analysis and a manual sampling process, donations from addresses that were associated with these types of behaviors were excluded for the purposes of matching calculations. This includes things like:
- Suspected bot activity based on specific transaction patterns and similarities
- ​​Flagging known Sybil networks/addresses from prior rounds
- Enhanced analysis of Passport stamps and other data to flag evidence of abuse between different wallets
- Self-donations from grantee wallets
Any details on the Legos used to identify the transaction patterns and similarities, the addresses squelched (we could put this in a private location if that was preferred - the OpenData Community keeps certain suspect Sybil addresses access controlled for example), and other explanations of the “enhanced analysis” and so on would be useful.
Soap box - and the nuance may be lost here - I’m 100% confident that great analysis was done. I’m also pretty sure that non-transparent analysis puts at risk the credibility we are all seeking to build or maybe rebuild in the space. By sharing more of how the analysis was done we can all gain confidence while learning more about how to protect rounds in the future.