grants/w3p-02.mediawiki

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Background: privacy-centric narrations around web3 are full of controversies & biases generated not just by anti-privacy people but privacy experts. It impacts privacy storytelling that's still related to crime &/or "nothing to hide" communication. At the same time, the market lacks deeper research on privacy narrations & a system breakdown of all existing stereotypes & biases.
==Phases==
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* Existing web3/crypto privacy narration research.
* Handbook for web3 privacy advocacy.
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==Phase 1: Existing web3/crypto privacy narration research==
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Delivery: research on industry narration around privacy from media coverage to professional opinions.
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=Goal=
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* to map down privacy storytelling within the industry
* to cover privacy narration & web3/crypto within external agents
* structure framing, biases, vocabulary - make a foundation for a re-framing
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=Areas of interest=
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=internal gaze=
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* How media frame privacy.
* Differences within expert takes on privacy.
* Existing privacy-centric vocabulary.
* Privacy advocates comms directions.
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=external gaze=
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* How media & governments frame privacy.
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* What privacy biases exist.
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**Approach**
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Traditional media studies approach that researches both quantitative & qualitative narrations around subject.
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=Categorised=
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* positive, negative, neutral framing filters (tonality)
* vocabulary segmentation
* relations within framing (Tornado Cash + North Korean hackers)
* quantitative statistics
* privacy agents map (roles, relation to industry, pro / anti status)
* text-based, visual content
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==Phase 2: Handbook for web3 privacy advocacy==
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Delivery: an actionable handbook for privacy advocacy.
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=Details=
Research will help to make an actionable handbook for privacy advocacy rooted in re-framing existing toxic storytelling. Moreover, it will give instruction & positive narrations to sceptics (like Aztec co-founder stating that people don't need privacy). Think of this as a "privacy brandbook".
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=Goal=
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* have a easy to execute document for various audiences to become privacy advocates
* fact & stats accuracy helps to unify storytelling within multiple agents: media, experts, community
* helps to raise awareness about state of privacy storytelling within industry & beyond
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=Format=
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* GitHub wiki
* PDF