On-Chain Social Graphs with On-Chain Moderation vs Federated Moderation

On-Chain Social Graphs with On-Chain Moderation excels at providing cryptographic verifiability and censorship resistance because every action—from posting to flagging—is a transparent, immutable transaction. For example, protocols like Lens Protocol and Farcaster store social graphs and key interactions directly on Polygon and Optimism, leveraging their sub-cent transaction fees and high TPS (e.g., Optimism's ~2,000 TPS) to make moderation actions like community-downvoting a programmable, on-chain event. This creates a trustless, global rulebook but introduces latency and cost for every moderation decision.

Federated Moderation takes a different approach by decentralizing authority across semi-autonomous servers (instances). This strategy, pioneered by ActivityPub-based networks like Mastodon and Bluesky's AT Protocol, results in a trade-off: it achieves massive horizontal scalability and near-zero per-action costs, as seen with Mastodon's 14M+ users, but at the expense of global consistency. Each instance (example.social) enforces its own rules, leading to fragmentation and potential for user exile rather than protocol-level adjudication.

The key trade-off: If your priority is sovereignty, anti-fragility, and building a unified, tamper-proof reputation layer, choose an on-chain model. This is critical for financialized social apps or DAO governance. If you prioritize user-scale growth, low-friction onboarding, and community-led cultural nuance, choose a federated model. Your choice ultimately hinges on whether you view moderation as a feature of consensus or a function of community.

On-Chain Social Graphs with On-Chain Moderation excel at providing cryptographic guarantees and composability. Because moderation actions (e.g., bans, content flags) are recorded as immutable transactions on a ledger like Ethereum or a high-throughput L2 like Base, they create a transparent, permissionless, and portable reputation layer. For example, a user's standing from a Farcaster client can be programmatically verified by any other dApp, enabling trustless integrations. This model is ideal for protocols prioritizing censorship resistance and building decentralized social primitives where data sovereignty is non-negotiable.

Federated Moderation (e.g., ActivityPub, Bluesky's AT Protocol) takes a different approach by decentralizing authority to independently operated servers (instances). This results in a trade-off: it achieves superior scalability and nuanced local governance—individual communities can set their own rules without global consensus—but at the cost of fragmentation and potential for instance-level censorship. A Mastodon instance with 100k users can moderate efficiently without incurring on-chain gas fees, but a user banned from a major server faces significant network effects loss, as their social graph isn't portable across the federation without explicit bridging.

The key trade-off is sovereignty versus scalability at the application layer. If your priority is maximizing user sovereignty, enabling permissionless innovation with smart contracts, and building a unified global graph (critical for DeFi-social integrations or NFT-gated communities), choose an on-chain model like those used by Lens Protocol or Farcaster. If you prioritize handling massive user bases with low latency, enabling diverse community rule-sets, and avoiding blockchain transaction costs and finality delays, a federated architecture like Bluesky's AT Protocol or a traditional ActivityPub implementation is the pragmatic choice. For CTOs, the decision hinges on whether your product's core value is derived from blockchain-native properties or from scalable, familiar social networking.