On-Chain Social Graph

An on-chain social graph anchors user identity to a cryptographic wallet address, creating a persistent, self-sovereign profile. Reputation is built through provable, on-chain actions like token holdings, governance participation, or transaction history. This creates a portable, sybil-resistant identity that can be used across multiple applications without re-establishing trust.

Social connections (follows, likes, memberships) are stored as public, permissionless data on the blockchain. This allows any application to read, interpret, and build upon the same underlying social graph. A user's network and activity on one platform (e.g., a decentralized social app) can instantly inform their experience in another (e.g., a DeFi or gaming application), enabling cross-protocol personalization.

Unlike traditional platforms where the company owns the network, an on-chain social graph is owned and controlled by the users. Relationships are not locked inside a single application's database. Users can export their social graph, migrate it to a new front-end interface, or grant specific applications temporary access, reversing the traditional platform-user power dynamic.

Core social functions are implemented as smart contracts, making them transparent and customizable. These social primitives include:

• Follow NFTs: Tokenized follow relationships that can be traded or grant access.
• Token-Gated Communities: Groups where membership requires holding a specific NFT or token.
• On-Chain Messaging: Communication recorded on-chain for provenance and integration with DeFi actions.

By linking social activity to wallet addresses with financial and transactional history, on-chain graphs provide inherent sybil resistance. Trust can be algorithmically derived from provable capital stakes (e.g., token holdings), transaction volume, or attestations from other trusted identities. This enables systems like decentralized credit scoring or collateral-light lending based on social capital.

Key protocols building this infrastructure include:

• Lens Protocol: A composable social graph on Polygon where profiles are NFTs and interactions are recorded on-chain.
• Farcaster: A sufficiently decentralized social network with an on-chain identity registry and off-chain data hubs for scalability.
• CyberConnect: A social graph protocol focusing on data sovereignty and cross-chain compatibility. These demonstrate the practical implementation of user-owned social data.

Interoperability in the on-chain social graph relies on shared data schemas and standards. Key models include:

• ERC-6551: Allows NFTs to own assets and interact as smart contract accounts, enabling richer profile functionality.
• ERC-721 & ERC-1155: Used for representing unique profile identities (like Lens Profile NFTs).
• Verifiable Credentials (VCs): Standards for issuing and verifying attestations (e.g., proof of skill, membership) that can be linked to an on-chain identity.

Protocols make distinct choices balancing decentralization, scalability, and user experience:

• On-Chain vs. Off-Chain Data: Storing all data on-chain (DeSo) maximizes ownership but faces cost/scalability limits. Hybrid models (Farcaster, CyberConnect) keep critical identity on-chain and social data off-chain.
• Composability: Protocols like Lens treat social actions as transferable NFTs, enabling new applications like social trading or collateralization.
• Client Diversity: A healthy ecosystem requires multiple independent clients (like on Farcaster) to prevent a single point of control or failure.

An on-chain social graph decouples social data from centralized platforms, storing connections and reputations as verifiable credentials on a public ledger. This creates a self-sovereign identity where a user's network, followers, and content interactions are owned by the user and can be ported across any application that reads the graph.

• Key Mechanism: Uses a user's cryptographic address (e.g., 0x...) as the root identity node.
• Example: A user's follower list on one social dApp automatically populates when they connect their wallet to a new, compatible platform.

On-chain graphs enable algorithmic discovery and content curation without platform intermediaries. Applications can programmatically query the graph to surface content based on provable social proof.

• Sybil-Resistant Ranking: Content or accounts can be ranked by the stake-weighted connections of their followers, not just raw follower counts.
• Example: A discovery feed that shows posts highly mirrored by addresses that also hold specific DAO governance tokens, indicating relevance to a specific community.

Social graph data serves as a foundational reputation layer for other Web3 applications. Connections and interactions become verifiable signals for granting access or privileges.

• Gated Communities: A DAO or token-gated group can require members to have a minimum number of verifiable followers from a trusted set of addresses.
• Credit & Underwriting: DeFi protocols could use the strength and longevity of an on-chain social network as a factor in soulbound credit scoring or undercollateralized lending.

Storing rich social data (posts, images, videos) directly on-chain is prohibitively expensive. Most implementations use a hybrid storage model.

• On-Chain: Stores the essential graph structure—addresses, connection hashes, and content pointers—as immutable metadata.
• Off-Chain: Stores the actual content (text, media) on decentralized storage networks like IPFS or Arweave. The on-chain record contains a cryptographic hash (CID) pointing to this data, ensuring integrity.

SocialFi (Social Finance) refers to applications that merge social networking with financial mechanisms, enabled by an on-chain social graph. It monetizes social capital directly through tokens and smart contracts.

• Creator Monetization: Creators can tokenize their community, offer subscription NFTs, or receive direct payments integrated into their social graph.
• Example: A creator's "collect" post function lets followers mint the post as an NFT, with proceeds going to the creator. The transaction and ownership are recorded on the social graph.

A core tension exists between the immutable, public nature of blockchains and user privacy. While interactions are pseudonymous by default, sophisticated analysis can deanonymize users by linking wallet addresses to real identities via on-chain activity patterns. Solutions include:

• Zero-Knowledge Proofs (ZKPs) for proving social connections without revealing them.
• Data encryption with user-held keys for private content.
• Data minimization, storing only essential relationship proofs on-chain.

Preventing fake accounts (Sybils) from manipulating the graph is critical for trust. Common mechanisms include:

• Proof-of-Humanity or Proof-of-Personhood verification.
• Stake-weighted or activity-based reputation systems.
• Social attestations where trusted connections vouch for new users.
• Cost-based barriers like transaction fees or token bonding curves. Without these, the graph becomes vulnerable to spam and coordinated attacks.

A key design goal is enabling users to move their social data between applications. This requires standardized data schemas (e.g., ERC-721 for NFTs, ERC-4337 for accounts) and composable smart contracts. Challenges include:

• Resolving conflicts between different application logic layers.
• Ensuring backward compatibility as standards evolve.
• Managing data sovereignty—who controls the mapping between an identity and its social data?

Decentralization aims to prevent unilateral censorship, but malicious content requires moderation. This creates a design paradox. Implementations balance this via:

• Algorithmic curation based on user-defined or community-driven filters.
• Delegated moderation with token-weighted voting.
• Layer separation, where the base protocol is neutral and applications implement their own moderation.
• Allow/block lists stored on-chain as non-transferable tokens.

Storing and querying graph data on-chain is expensive. High gas fees on base layers like Ethereum can make social interactions prohibitive. Scaling solutions include:

• Layer 2 Rollups (Optimistic, ZK) for cheaper transactions.
• Application-specific sidechains.
• Hybrid architectures storing only critical proofs on-chain (e.g., follow attestations) with bulk data on decentralized storage (IPFS, Arweave).
• State channels for off-chain, high-frequency interactions.

Deciding how the protocol evolves without centralized control is a critical design consideration. Models include:

• Token-based governance (e.g., DAOs) for protocol parameter changes.
• Multi-sig councils for emergency interventions.
• Immutable core contracts with modular, upgradeable extensions.
• Social consensus among key ecosystem participants (developers, users, node operators). Poor governance can lead to protocol forks or stagnation.

A self-sovereign identity standard that allows users to own and control their digital identifiers without relying on a central authority. DIDs are a foundational component for building a portable, user-centric social graph.

• Key Standards: W3C DID, Verifiable Credentials.
• Use Case: A user's DID can link their activity across multiple dApps, creating a unified, user-controlled profile.

A category of applications and protocols built on blockchain that enable social networking features like profiles, posts, and follows, with data stored on a public ledger.

• Core Principle: User-owned social capital and content.
• Examples: Protocols like Lens Protocol and Farcaster provide the infrastructure for DeSo applications, where social connections are assets.

Non-transferable non-fungible tokens (NFTs) that represent credentials, affiliations, or achievements tied to a specific wallet address. They act as verifiable, composable data points for the social graph.

• Function: Represent membership, event attendance, or skill certifications.
• Graph Impact: SBTs create a rich, attestation-based layer of identity and reputation that other dApps can query.

The technical process of querying and structuring raw blockchain data (follows, likes, mentions) into a usable graph database. This enables efficient discovery of connections and patterns.

• Infrastructure: Often handled by The Graph Protocol subgraphs or custom indexers.
• Output: Provides APIs for applications to easily fetch a user's connections, content, and social context.

Mechanisms designed to prevent a single entity from creating multiple fake identities (Sybils) to manipulate a network. This is a critical challenge for trust in on-chain social systems.

• Solutions: Include proof-of-personhood protocols (e.g., Worldcoin), attestation networks, and stake-based reputation.
• Goal: Ensure that nodes in the social graph correspond to unique, credible human or entity-backed actors.

The ability for different applications to freely read, use, and build upon the same set of on-chain social data. This is a core value proposition of a public social graph.

• Benefit: A user's social connections and reputation built on one platform (e.g., a DeSo app) can be utilized by a completely separate DeFi or governance application.
• Contrast: Unlike Web2, data is not siloed within a single company's database.