explorer/Web3privacynowplatform/scoringmodel
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Readme.md

Scoring model analytics based on a 50+ privacy projects survey

We are shipping an educational website to help the general public understand whether a web3-service is private or not. Its core feature - scoring mechanism validated by the market (reference: web3 - l2beat, web2 - IMDB).

Original idea Privacy market survey Scoring model MVP Community feedback model 1.1 ETHRome data set DeFi category scoring x model 1.2 Playbook for non-techies 1.3
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17 Oct, 2023 update

2 DO list

Analyze

Create

  • Github page in this repo
  • Enrich scoring model MVP with the new parameters that could be easily automated or quickly manually aggregated (if not - move data set into a backlog)
  • Try to apply previous scoring model approach (with % &/or semaphore take: green, yellow, red) to new parameters & observe how scoring model could change (write down potential changes & implications)

Delivery

  • Final page will be breaken down into:
    • Updated scoring model MVP data set (without scoring approach)
    • Simulation of the old MVP + new MVP: how scoring could change with new parameters
  • Backlog (data that can't be quickly parsed)

Backlog