[PASSED] GG20 Program Round Matching Results

I was intrigued by this and thought of digging deeper into the data. I would like to think the following supports @Joel_m’s assertion about donor diversity.

I profiled BerryLab’s top 50 donors compared to the other project (with fewer contributors/contributions, let’s call it Project A). The top 50 donors of Project A collectively supported 152 out of the 153 projects in the dApps & Apps round, while the top 50 donors of BerryLab have contributed to 34 out of the 153 projects. In relative terms, the top contributors for Project A are likely to be part of more diverse clusters by a long shot.

While this is not conclusive, it is a directionally indicative reason behind the difference. I have spot-checked this with 3 other projects with less than 100 unique voters contributing to less than $350 in crowdfunding but have received an average matching Per Voter > $15. In each case, their top 50 donors collectively support at least 120 or more projects in the round.

(Query to support this analysis is available in the Metabase instance of Regendata here).

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Nice way of thinking, I second to that :slightly_smiling_face:

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Just raising this again as it is blocking my analysis.:grimacing:

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Hey! 100 is good. We apply a sliding scale to donations based on the passport score. If your score is 0 you get no matching. If your score is 1 you get 50% matching, and this increases linearly until a score of 25 at which point you get 100% matching. The amountUSD is the value after this scale is applied while the startingAmountUSD is the original donation.

I’m looking into the bug in the registration process. If you DM me a good email address I can add you manually for now. I’m @umarkhaneth on tg

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Ok, here are some graphs that may help @Moeen , @CryptoRohittt , and @ayush035 understand their funding outcomes.

We’ve mentioned above and in other communications how COCM prioritizes projects with diverse sets of donors. The charts below give one way of visualizing that on GG20 data.

Each dot on these scatterplots is one project. The X axis is the average diversity of that project’s donors, and the Y axis shows the amount that project benefited from moving from standard QF to COCM.

In more detail: to calculate the X axis number, we looked at all pairs of donors to a project. For each pair, we found the number of other projects that just one person out of the pair donated to, and averaged all those numbers. To calculate the Y axis number, we found the percent of the matching pool that project got under COCM, and divided that by the percent they would’ve captured under standard QF. Also, since the DApps round was so big, we used 10k randomly sampled pairs instead of all pairs, per project.

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These scatterplots show a correlation between this particular measure of donor diversity and project success. They might also help to explain why BerryLab, WalletX, and Stogram performed less well than expected: in regards to this measure, they’re on the lower end of the distribution, coming in at 9.57, 4.97, and 10.64 respectively.

Hopefully these charts can be helpful to everyone trying to understand why funding results look the way they did, and can help all of us in the Gitcoin community understand how we want to align the algorithm in the future. I would love everyone’s feedback on whether or not this is the type of behavior we want out of the algorithm, and why or why not that’s the case.

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Thank you for providing this data and taking the time to explain all the details. I think it might be beneficial to exclude the outliers for each project. This could help to eliminate any potential bias if a random wallet only donated to one project.

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Got it , I appreciate your efforts for helping us understand COMC ,things makes much more sense now.

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Hi @skilesare – could you send me the addresses of the 46 carpet bombers you mention? Email is the best way – joel@gitcoin.co

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hey @umarkhaneth , since $EARTH was rejected initially and then we got through after making the necessary changes for the OSS round, there were 2 grants LIVE - the one that got rejected and the one with which we reapplied.

Have been given to believe that votes given to only of the 2 live are getting counted.

Any particular reason not to include votes to both ?

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Hey @solarpunkmaxi, our program automatically pulls data on accepted projects and calculates the matching results. Including the votes from a rejected project and/or combining votes on two projects means a manual intervention.

With that said, we’ve gone ahead and processed this for $EARTH in the Dapps round and for DSPYT (who reached out via telegram and also had a duplicate project situation) in the Hackathon round.

The updated results are live in the results sheet.

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To confirm: there are still no donations in the wallets connected to the #GG20 grant until the QF has been calculated?

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The vote to ratify the GG20 results is now live on snapshot and running until May 28th! Please go vote! :ballot_box:

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No all crowdfunded donations are already in grantee wallets. If you’re having issues pls dm me on telegram @umarkhaneth

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Why speculate? just share the data with us!

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reposting these links from above

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Sent the list last week but just noticed my message didn’t post. Did you receive it via email?

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This snapshot has closed and option to “Ratify the round results” has won.

Metrics:
1,635 unique wallets voted
~4.9M GTC tokens cast.

Thank you to all who voted!

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@Joel_m Did you ever have a chance to look at that list? Still trying to figure out what went wrong and how I can do better next round.

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Hi @skilesare, sorry for the delay here.

I re-ran the results with the “carpet bombers” you indicated removed from the donor pool. Removing them doesn’t seem to significantly change outcomes – in particular, your project does get more matching, but only an additional 0.00000027 of the funding pool.

I also tried stress-testing the results by adding in up to five thousand more fake carpet bombers, to see if this can become a viable attack with many such accounts. With 5k carpet bombers added in, your project’s share of the matching pool does decrease, but only by a fraction of 0.0000021 (compared to the world with all carpet bombers removed).

That being said, these seem to be very different results than what you noted in your original post. If you’re comfortable emailing me with further information about what numbers you crunched to get the results you did, please shoot me another email.

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Joel…I think this is just a case of most of my contributions being at opposite ends of the spectrum. Most of my donors were coming from outside the ETH ecosystem. Hopefully they are more established now and will get better scores in the next go around. We’ll just have to build it up over time.

We do have a cool demo of bringing passport over to our community now, so hopefully I can get better engagement with it in the future: Demo – Bring the Gitcoin Passport Score to the Internet Computer

I’m also lobbying to get ckGTC enababled, but we likely need a good use case first. :slight_smile: ic/rs/ethereum/cketh/docs/ckerc20.adoc at master · dfinity/ic · GitHub