The success of decentralized social protocols is not solely the result of a single technological breakthrough, but rather the outcome of the collaborative evolution of three key dimensions: identity, storage, and discovery.
Written by: Centreless
In the Web2 era, social networks were platform-centric, with user data locked within closed ecosystems, algorithmic recommendations controlled by giants, and identities tied to platform accounts. The vision of Web3 is to build an open, composable, user-sovereign social infrastructure. Whether this vision can be realized depends on whether its underlying architecture truly achieves decentralization.
Current industry consensus holds that the underlying structure of decentralized social protocols is built around three core dimensions: identity system (Account / ID), data storage (Storage), and search and discovery mechanisms (Search & Recommendation). These three dimensions not only jointly determine the degree of decentralization of the protocol but also profoundly influence its long-term evolutionary path.
This article will delve into the mechanisms of these three pillars, outline the key breakthroughs achieved in the identity and storage layers, and focus on why the search and recommendation mechanism will become the core variable determining the future explosive potential of social protocols.
How do the three dimensions determine the degree of decentralization and evolutionary direction?
1. Identity System: The Cornerstone of User Sovereignty
In traditional Web2 social platforms, user identities are assigned by the platform (e.g., Twitter username, WeChat ID), lacking cross-platform portability, and accounts can be banned at any time by the platform. This "tenant-style identity" deprives users of their digital sovereignty.
The Web3 identity system seeks self-sovereign identity (SSI), where users have complete control over their identities, including creation, management, verification, and migration. Typical representatives include ENS (Ethereum Name Service), Lens Protocol's Profile NFT, and Farcaster's Custody + Signer architecture. These solutions enable user identities to break free from single platform control through cryptographic keys, on-chain registration, or NFT-based identities.
Degree of decentralization reflects: whether identities are verifiable, portable, immutable, and can be created without permission. Evolutionary direction impact: a robust identity system supports the reuse of cross-application social graphs, promoting "social composability" and forming a network effect flywheel.
2. Data Storage: The Guarantee of Content Sovereignty
Web2 platforms concentrate user-generated content (UGC) in private servers, preventing users from truly owning their data. In contrast, Web3 emphasizes that data ownership belongs to users, with protocols only providing read and write interfaces.
Decentralized storage solutions like IPFS, Arweave, and Ceramic Network allow social content (posts, comments, follow relationships) to be stored persistently and censorship-resistant, referenced through DID (decentralized identifiers) or on-chain pointers. For example, Lens Protocol stores post metadata on IPFS and records CID (content identifier) through smart contracts; Farcaster uses Merkle trees to anchor messages on-chain, with actual data distributed for storage.
Degree of decentralization reflects: whether data is auditable, transferable, censorship-resistant, and whether users can autonomously delete or transfer it. Evolutionary direction impact: an open data layer spawns third-party clients, analytical tools, and derivative applications, forming a "protocol + ecosystem" model rather than "platform monopoly."
3. Search and Discovery Mechanism: The Engine of Network Effects
Even with decentralized identities and open data, if users cannot efficiently discover content and connect with others, the protocol will fall into a "stagnation" state—having infrastructure but lacking an active ecosystem. The core moat of Web2 is its personalized recommendation algorithms (e.g., TikTok's recommendation engine, Twitter's For You Feed).
In Web3, search and recommendation face dual challenges:
Technical aspect: It is difficult to build high-performance, low-latency indexing and ranking systems in a decentralized environment;
Governance aspect: If the recommendation logic is controlled by a single entity, it contradicts the spirit of decentralization; if completely open, it may be abused or inefficient.
Therefore, the design of search and discovery mechanisms directly determines:
Whether new users can quickly integrate into the community;
Whether quality content can be effectively distributed;
Whether the protocol has viral growth potential.
Degree of decentralization reflects: whether recommendation algorithms are transparent, auditable, customizable, and competitive (multiple recommendation engines coexisting). Evolutionary direction impact: it determines whether the protocol can transition from "geek toys" to the mass market, being a key variable for scaling.
Major Breakthroughs in Identity System and Data Storage Layer
(1) Identity System: From Wallet Address to Semantic Social Identity
Early Web3 identities were merely represented as a string of hexadecimal wallet addresses (e.g., 0xAbC…), resulting in a poor user experience. In recent years, several breakthroughs have emerged:
ENS (Ethereum Name Service): Maps Ethereum addresses to human-readable names (e.g., vitalik.eth), becoming the de facto standard for Web3 identity, with over 8 million registrations.
Lens Protocol: NFT-izes social identities, with each Profile being an ERC-721 asset that users can fully own and trade their social graphs.
Farcaster: Adopts a "on-chain registration + off-chain signing" hybrid model, allowing users to register identities through Ethereum addresses, with daily operations broadcast off-chain via EdDSA signatures, balancing security and performance.
Worldcoin / Gitcoin Passport: Introduces Sybil Resistance mechanisms, enhancing identity credibility through biometrics or behavioral proofs, providing a foundation for decentralized governance and airdrop distribution.
These solutions collectively drive the evolution of identity from "anonymous addresses" to "verifiable, composable, and trusted" social entities.
(2) Data Storage: From Temporary Cache to Permanent Verifiable Records
Decentralized storage technology has significantly matured in recent years:
Arweave: Offers "permanent storage" services, with a one-time payment for data that is permanently accessible. Writing platforms like Mirror.xyz rely on Arweave for article storage.
Ceramic Network: Constructs dynamic data streams, supporting real-time updates in decentralized databases, suitable for social graphs, comments, and other high-frequency interaction scenarios.
IPFS + Filecoin: IPFS provides content addressing, while Filecoin offers an incentive layer to ensure storage persistence, already adopted by projects like Lens and Orbis.
Tableland: Combines SQL databases with EVM smart contracts, allowing on-chain logic to operate on off-chain table data, enhancing the efficiency of social application development.
These infrastructures make "user ownership of data" no longer just a slogan, but a tangible technological reality.
Search and Recommendation Mechanism: The Key Variable Determining Explosive Potential
Despite progress in identity and storage, search and discovery remain the biggest bottleneck for Web3 social. The reasons are as follows:
1. High Technical Complexity
Decentralized networks lack a unified index, requiring the construction of distributed crawlers and aggregation layers (e.g., The Graph is used for querying on-chain data but has limited support for off-chain social content).
Real-time recommendations require low-latency computation, while most decentralized storage read speeds are far below centralized CDNs.
Personalized recommendations rely on user behavior data, but in a privacy-first Web3 environment, data collection is restricted.
2. Incentive and Governance Challenges
Who will run the recommendation engine? If operated by the protocol's official team, the risk of centralization re-emerges;
If opened to third parties, a reasonable incentive mechanism must be designed (e.g., token rewards for indexers);
If recommendation algorithms can be manipulated (e.g., through fake likes or follows), it will lead to a decline in information quality.
3. Huge User Experience Gap
Web2 users have become accustomed to "personalized recommendations" tailored to individual preferences. However, most current Web3 social applications still remain at the "reverse chronological timeline" or "popular rankings" stage, lacking deep personalization, resulting in low retention rates.
Breakthrough Directions: Modular and Composable Discovery Layer
The industry is exploring various innovative paths:
Decentralized indexing protocols: such as The Graph extending support for Ceramic data streams, Airstack.
Building unified identity and social graph APIs.
Pluggable recommendation engines: users can choose different recommendation algorithms (e.g., "by interest," "by region," "by DAO members"), similar to browser plugins.
AI + Zero-Knowledge Proofs: Utilizing ZK technology to achieve personalized recommendations while protecting privacy (e.g., zkML).
Community-driven discovery: incentivizing users to participate in content curation through tokens (e.g., Farcaster's Warpcast client introduces "channels" and "trending topics").
Semantic search experiments: such as Lens Protocol collaborating with AI companies to attempt searches based on content semantics rather than tags.
Key Insight: The future winner may not necessarily be the "best protocol," but rather the "protocol with the best discovery mechanism." Because only by continuously showing users valuable content can a positive feedback loop be formed, driving exponential growth in network effects.
Conclusion: The Collaborative Evolution of the Three Pillars
The success of decentralized social protocols is not solely the result of a single technological breakthrough, but rather the outcome of the collaborative evolution of three key dimensions:
The identity system empowers user sovereignty;
Data storage guarantees content freedom;
Search and recommendation activate network value.
Currently, the first two have begun to take shape, while the latter remains in a "no man's land." For this reason, search and recommendation mechanisms will become the main battleground for the next phase of Web3 social innovation. Whoever can first build a discovery engine that is both decentralized and efficient may replicate or even surpass the growth trajectory of Web2 social giants, truly ushering in a new era of open social networks belonging to users.
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