Social Graph Protocol

Users own their social graph data, stored on a decentralized network (like Arweave or IPFS) or directly on a blockchain (like Ethereum L2s). This contrasts with traditional platforms where the company owns the network data. Users can port their connections and reputation across different applications built on the same protocol, breaking platform lock-in.

Social graphs are built as open, programmable data layers. Developers can read from and write to the graph using standardized schemas and APIs, enabling:

• Cross-application functionality: A follower list from one app works in another.
• Custom relationship types: Beyond 'follows', define connections like 'endorsed', 'collaborated with', or 'staked in'.
• Graph queries: Applications can programmatically traverse the network of connections.

Relationships and social actions are often represented as verifiable, on-chain attestations. These are cryptographically signed statements (e.g., 'Wallet A follows Wallet B') that are immutable and publicly auditable. Protocols like Ethereum Attestation Service (EAS) or Verax provide the infrastructure for this, turning social signals into provable on-chain credentials.

Protocols leverage on-chain activity and proof-of-personhood systems to mitigate fake accounts and spam. Reputation is often derived from verifiable actions like:

• Token holdings & governance participation
• Transaction history and network age
• Attestations from other trusted identities This creates a social graph where connections carry more weight than on anonymous web2 platforms.

Economic models are baked into the protocol layer to align incentives. Features include:

• Native tokens for governance and fee payment.
• Staking mechanisms to signal trust or curate content.
• Direct value transfer between connected entities (e.g., tipping, paid subscriptions).
• Protocol-level revenue sharing with data contributors, unlike web2 models where value is captured centrally.

Different protocols emphasize various aspects of the social graph:

• Lens Protocol: A composable, EVM-based social graph focusing on profile NFTs and portable follower relationships.
• Farcaster: A sufficiently decentralized social network protocol with an on-chain registry and off-chain hubs for data storage.
• CyberConnect: A social graph protocol emphasizing data sovereignty and developer tooling across multiple blockchains.
• ENS (Ethereum Name Service): While primarily a naming system, it provides a foundational, verifiable identity layer for social graphs.

Underlying technical standards that enable social graph interoperability and composability.

• ERC-721 & ERC-1155: NFT standards used to represent profiles, posts, and subscriptions.
• EIP-4844 (Proto-Danksharding): Reduces data availability costs for social transactions via blobs.
• GraphQL: The predominant query language for indexing and retrieving complex graph data from protocols like The Graph.
• Verifiable Credentials: Standards for issuing and verifying attestations of reputation or membership.

Practical applications built atop social graph protocols, demonstrating their utility.

• Decentralized Social Media: Apps like Phaver, Orb, and Yup aggregate content from multiple protocols.
• On-Chain Reputation & Governance: Voting power based on social graph influence or community contributions.
• Targeted Airdrops & Marketing: Identifying engaged user cohorts based on their graph connections.
• Discovery Engines: Finding relevant content or communities through algorithmically curated feeds derived from the graph.

At its foundation, a social graph protocol defines a schema for relationship data, often using a graph model where nodes represent entities (e.g., wallets, profiles, DAOs) and edges represent connections (e.g., follows, likes, attestations). This data is stored on-chain or in decentralized storage, making it publicly verifiable and permissionlessly accessible for any application to query and build upon.

These protocols enable portable identity and on-chain reputation. Instead of social data being locked inside a single platform (like Twitter or Facebook), a user's connections, endorsements, and community memberships are owned by their wallet. This allows for:

• Sybil-resistance through web-of-trust models.
• Reputation-based governance weighting in DAOs.
• Credentialing systems where attestations from trusted entities carry verifiable weight.

Social graph protocols create a composable social layer, analogous to how DeFi protocols compose for financial legos. This enables a new "social stack":

• Base Layer: The protocol (Lens, Farcaster) storing the graph.
• Middleware: Indexers, algorithms, and data tools (e.g., The Graph for querying).
• Application Layer: Independent clients, curation feeds, and analytics dashboards that all read from and write to the same underlying social data.

Beyond replicating traditional social media, these protocols enable novel blockchain-native applications:

• Community Management: Automated role assignment in Discord based on on-chain follows or attestations.
• Trusted Launchpads: Allowing token sales only to wallets with a proven reputation or specific community affiliations.
• Decentralized Curation: Algorithmic feeds where the ranking logic is transparent and governed by token holders, not a corporate entity.
• Cross-Platform Identity: A single, aggregated social profile that works across multiple dApps and games.

A database that uses graph structures (nodes, edges, properties) to represent and store data. It is the optimal backend for querying complex social relationships inherent in a social graph protocol.

• Nodes: Represent entities (users, posts).
• Edges: Represent relationships (follows, likes, replies).
• Query Language: Often uses GraphQL or specialized languages like Cypher (Neo4j) or Gremlin.
• Benefit: Enables efficient traversal of multi-hop connections (e.g., "friends of friends").

The guarantee that data (like social graph state updates) is published and accessible for network participants to download. It's a critical layer for decentralized social networks to ensure censorship resistance and verifiability.

• Core Problem: Ensuring data is stored and retrievable without a central server.
• Solutions: Data Availability Layers (e.g., Celestia, EigenDA) or Decentralized Storage (e.g., Arweave, IPFS).
• Importance: Nodes must be able to sync the latest social interactions to reconstruct the graph state.