Plurality Network
  • Overview
  • What is Plurality Network?
    • Layer 3 - The Open Context Layer
    • Smart Profiles
  • The Core Protocol
    • Core Mechanics of a Smart Profile
    • Structure of a Smart Profile
    • Chain Abstraction
    • Zero Knowledge Proofs
    • Personal AI
  • Concepts
    • Web2 Data and Login
      • Digital Footprint
        • Reputation and Interests
      • Login Mechanism
    • Web3 UX Challenges
      • Wallet Abstraction
      • Chain Abstraction
      • Fragmentation
      • Cold Start Problem
      • Network Effects
    • Web3 Data and Login
      • Data
      • Login
    • Data Ownership
  • Use Cases
    • Easy Login
    • Universal Reputation
    • Social Communities
    • Personalization
    • Profile Gating
    • DAO Governance
    • Sybil Resistance
    • Airdrop Whitelisting
    • Interoperability
    • Proof of Social Reputation
    • Cross Platform Experiences
    • Engagement and Loyalty
  • Developer Guides
    • Wallet Integration
    • Wallet SDK
    • Smart Profiles SDK
    • Server Side Sessions
  • Tokenomics
  • Products
    • Smart Profiles Wallet
  • Resources and Support
    • Workshops and Sessions
    • Explorers
    • Demos
  • Ecosystem
    • Apps Marketplace
    • Participate
      • Hack'n Heights Hackathon (May '24)
  • Contact Us
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  • Reputation
  • Interest

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  1. Concepts
  2. Web2 Data and Login
  3. Digital Footprint

Reputation and Interests

PreviousDigital FootprintNextLogin Mechanism

Last updated 6 months ago

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A user's reputation and interests can be extracted from their online activity ().

Reputation

The reputation of a person online consists of the data tagged to the person that represents the skillset and capabilities of that person.

How a reputation is derived

How a reputation is derived

Some examples of reputation are:

  1. The DAOs you have been a part of and for whom you have voted on-chain

  2. The information on the LinkedIn profile represents the skill set of the profile owner

  3. The videos produced on YouTube or LivePeer represent the kind of content the profile owner has mastery over

  4. The questions and answers posted on StackOverflow represent the skill level of a developer on a certain technology

  5. The code commits on GitHub represent the tech stack expertise of the profile owner

  6. The portfolio on Behance or the NFTs held by a person shows the design sense of a designer

  7. The research papers and H-Index show the quality of research of a researcher

  8. The amazon seller ratings of a seller show the quality of product and service of a seller

etc.

Interest

The interests of a person can be extracted from the type of consumed content. Some examples of how interests can be extracted are:

  1. The token-gated communities user is a part of

  2. Topics of pages liked on Facebook

  3. Influencers followed on Instagram

  4. People followed on Lens or Farcaster

  5. Subreddits joined on Reddit

  6. Search history on YouTube

  7. Created playlists on SoundCloud

  8. Pinned images on Pinterest

  9. Channels joined on Discord

etc.

Overall, for any platform to reduce noise and curate user experiences, both the reputation and interests need to be taken into account.

digital footprint