Experimental Sybil Identification Method using Graph Deep Learning
Seeking funding to refine and validate an advanced deep learning method for sybil detection in Web3 governance, aimed at enhancing democratic decision-making and system integrity.User Review
AI Review
A1
Reviewed on 15 Feb 2024 06:43 AM
You are a researcher. To qualify for this round you need to have a track record of research. This can be as part of an academic affiliation or as an independent researcher. If you are applying for a grant for your first research project, email hello@metagov.org with more info on why you are the right person to conduct this research.
The researcher, Dr. Quinn DuPont, has an extensive publication record in the field and has previously completed a Gitcoin grant, indicating a solid track record of research.
Governance focus for the research. We will only accept grants that have a clear focus on governance. As noted in the description, you don’t necessarily need to focus exclusively on DAO or web3 governance, but your research needs to be applicable to decentralized governance broadly. A focus on Arbitrum or Uniswap is appreciated but not required.
The project aims to develop a method for identifying sybils in Web3 governance systems, which directly pertains to digital and decentralized governance challenges, thus fulfilling the governance focus requirement.
No for-profit funding. If you have received VC funding or any other kind of funding that requires a return on investment, then it will not qualify. It is ok if you’ve received other grants.
The project description indicates that it was initially funded by an academic institution, York University, and no for-profit funding sources have been listed. The researcher also discloses no personal crypto investment relevant to the project's funding.
No retrospective funding. The research must either be launched soon or currently ongoing. Completed projects are not eligible for funding in this round.
The project proposes funding for the next phase of research, indicating that it is currently ongoing and seeking support for future work rather than completed research.