Delete Web3privacynowplatform/Scoringmodel directory

Web3privacynowplatform/Scoringmodel/Readme.md

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-Scoring model analytics based on a 50+ privacy projects [survey](https://docs.google.com/spreadsheets/d/1JWpAsGL10UTsVeuIVbouzUxRjaSPUAamxcbFljXuUWE/edit?usp=sharing)
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-**Approach**:
-- we made a survey on how privacy projects recommend analysing if they are private or not.
-- answers were assembled into 1 Excel sheet to be further analysed
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-**Fileverse**	
-Answers:
-- open sourcing our work
-- you literally generate and download your own e2ee keys
-- documentation
-- social recovery options
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-_Observations_: 
-- open source non-techies should know what "open source" means & how to measure it (solution: Open source 101 education)
-- key ownership is another knowledge person should know (contrast: Google or Meta "owns" your ID/key) + e2ee 101 is a must here
-- clicking on the documentation link & understanding it are different skills
-- social recovery is a less techy assessment & is linked to a persona (data ownership)
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-_Product feature_
-- open source 101 (short version)
-- e2ee 101
-- documentation: exists/missing (+/-)
-- social recovery 101
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-**Lava Network**	
-Answers:
-- starting with our litepaper	
-- further questions feel free to drop them in our discord
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-_Observations_:
-- "read the docs" is a popular answer without any third-party attestation that docs are correct, care for privacy etc
-- Discord serves as a two-way comms platform (but depends on the project) & it creates additional dependence of user on the core team
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-_Product feature_
-- in the future: collab with a security audit companies to create a new docs audit service description when a third-party will attest privacy-features of the initial idea x tooling description
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-**Holonym**	
-Answers:
-- Check their website or docs	
-- If they vaguely say “data is kept private” and provide no explanation how, run	
-- If they provide an explanation, check with an expert or DYOR
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-_Observations_:
-- "check" is a highly abstract action related to the website or docs -> extract value should be related to understanding "privacy"-validity markers
-- "private data explainers" needed to be defined within use-cases (case studies for the market
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-_Product feature:_rk
-- website checklist (1-2-3-4-5..., yes/no validity)
-- case studies "private data" explainers
-- DYOR (that's our platform)
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