Exploring the Potential of EFP on EIP: Integrating Decentralized Influence Proof (DIP)

Abstract
In the Web3 ecosystem, influence is dispersed across different social networks and applications, lacking a unified measurement standard and cross-platform composability. Current influence measurement systems rely on centralized data sources, making them susceptible to manipulation and difficult to integrate across various Web3 applications. This paper explores the potential of integrating EFP with Decentralized Influence Proof (DIP) and how it can contribute to solving the problem of influence silos in Web3, providing a trusted influence measurement benchmark for social, DeFi, DAO, and NFT ecosystems under the Ethereum Improvement Proposal (EIP) framework.

Introduction

As the Web3 ecosystem develops, influence has become a key factor in determining an individual's standing on the blockchain. Whether in decentralized social networks (e.g., Warpcast, Lens) or DAO governance, a user's influence directly impacts their value within the network. However, Web3 influence currently faces the following core issues:

1. Cross-Platform Influence Silos

   • Existing Web3 social networks (e.g., Warpcast, Lens, Farcaster) and decentralized identities (e.g., ENS, DID) lack a universal influence measurement standard.
   • Users' influence on different platforms cannot be transferred, limiting the scalability of Web3 influence.

2. Non-Verification

   • Current Web3 influence mainly relies on centralized APIs (e.g., The Graph, social media platform data interfaces), which make it difficult to ensure data authenticity and censorship resistance.
   • Influence algorithms are often controlled by a single platform, lacking transparency.

3. Non-Composability

   • Web3 influence has yet to form a standard, causing DeFi, DAO, and NFT ecosystems to struggle with leveraging social influence as a basis for credit, governance, or recommendations.
   • Influence is not tied to assets, preventing it from being traded, rented, or staked like ENS domains.

4. Lack of Real-World Identity Binding

   • Influence credentials are difficult to bind to real-world identities (e.g., KYC verification), limiting DIP's application in financial and governance scenarios with higher stakes.

Therefore, by integrating DIP (Decentralized Influence Proof) with EFP, we can create a cross-platform, on-chain verifiable, composable influence standard that is universally applicable across the Web3 ecosystem and enhance its applicability within the EIP framework.

The Potential of EFP Integrated with DIP

Influence Mining Mechanism

• Concept: Influence Mining is a part of the DIP ecosystem that allows users to earn token rewards by increasing their influence.
• Mechanism: The contribution value is calculated based on users' interactions on the social network (e.g., likes, shares, content creation), and DIP tokens are distributed accordingly.
• Anti-Sybil Attack: ZK proofs and social graph analysis are employed to prevent fake interactions and bot abuse.
• Use Case: Users can trade, vote, govern, or stake the mined DIP tokens to gain further benefits.

Application of EFP in the EIP System

• Standardizing Influence Measurement: Submit the DIP influence calculation standard as an EIP, making it a universal protocol within the Ethereum ecosystem.
• Smart Contract Integration: By integrating EFP with DIP, it can serve as a standardized component for DAO governance and DeFi credit evaluation, improving fairness within the Web3 economy.
• NFT and Influence Binding: Influence calculated based on DIP can be used for NFT rankings, making the value assessment of NFT assets more transparent.

Future Prospects

The integration of EFP with DIP and its inclusion in the EIP system will promote fairness and decentralization within the Web3 ecosystem, turning influence into a verifiable asset. In the future, further research could focus on:

1. Influence Mining: Reward users based on the growth of DIP influence, turning Web3 influence into a tradable asset.
2. ZK Privacy Protection: Ensure the privacy of influence data, allowing users to choose when to disclose their DIP data.
3. Cross-Chain Compatibility: Support multiple chains to facilitate broader influence interoperability.
4. DIP Influence Market: Allow users to trade, rent, or stake DIP influence, making influence a liquid asset and driving the decentralized influence economy.
5. Multi-Dimensional Influence Scoring: Introduce different dimensions of influence in the DIP calculation standard, such as community contribution, social interaction quality, and cross-platform influence, to provide a more comprehensive Web3 influence profile.

Conclusion

Integrating EFP with DIP as a decentralized influence credential provides Web3 with a composable, verifiable influence measurement system. It offers new trust mechanisms for social, DAO, DeFi, and NFT ecosystems, fostering the growth of the Web3 influence economy and establishing a universal influence standard within the EIP framework.

Keywords: EFP, DIP, Decentralized Influence, Web3, EIP, DAO, NFT, DeFi, Social Identity