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zero-knowledge-privacy-identity-and-compliance
Blog

Why Private Social Graphs Will Win the Next Bull Run

The next bull market will be defined by user ownership. We analyze how privacy-enhancing protocols like zkLogin and Sismo enable compliant, high-value social graphs that will siphon users from extractive Web2 platforms.

introduction
THE PROTOCOL LAYER

The Great Unbundling of Social Capital

The next bull run will be defined by protocols that separate social data from monolithic platforms, enabling user-owned, composable reputation.

Social graphs are proprietary assets. Platforms like X and Facebook monetize user connections as a moat. Web3 protocols like Lens Protocol and Farcaster treat the graph as a public good, allowing users to port their network across applications.

Portable reputation creates new markets. A Lens follower graph becomes a Sybil-resistant identity layer for Aave's GHO or a curated allowlist for friend.tech keys. This composability unlocks underwriting and discovery that centralized platforms cannot replicate.

The data proves the shift. Farcaster's daily active users grew 50x in 2024, while its Frames standard turned casts into native app interfaces. This demonstrates demand for protocol-first social infrastructure where the client is irrelevant.

Evidence: The total value locked in social DeFi applications leveraging on-chain graphs surpassed $100M in Q4 2024, with projects like CyberConnect and Rarible integrating social data for NFT curation and airdrops.

thesis-statement
THE SOCIAL GRAPH

Thesis: Privacy is the New Premium Feature

Private, user-owned social graphs will capture the majority of value in the next cycle by solving the data monetization paradox.

User-owned social graphs are the new moat. Public on-chain activity is a liability, exposing trading strategies and network value. Protocols like Farcaster and Lens Protocol demonstrate that encrypted, portable social data creates unbreakable user loyalty and defensible business models.

Privacy enables premium monetization. Public data gets arbitraged; private data gets paid for. This reverses the Web2 ad-tech model. Users will pay for end-to-end encrypted social feeds and DMs, treating privacy as a utility, similar to how Telegram monetizes its platform.

The evidence is in adoption. Farcaster's Warpcast client achieved profitability through paid features, not ads. This proves a direct user revenue model works when you control the graph. The next bull run will fund protocols that build this infrastructure, not just speculate on tokens.

SOCIAL GRAPH ECONOMICS

The Surveillance Tax vs. The Privacy Premium

A first-principles breakdown of the economic and technical trade-offs between traditional and on-chain social models.

Core MetricLegacy Web2 Model (Surveillance Tax)On-Chain Public GraphOn-Chain Private Graph (e.g., Farcaster, Lens with ZK)

User Data Ownership

Developer Access Cost

$10k+/month (API)

Gas fees only

Gas fees + ZK proof cost (~$0.01-0.10)

Ad Revenue Capture by User

0%

0-5% (via tokens)

5-20% (via direct micropayments)

Sybil Attack Resistance

Centralized KYC

Token-bound cost (>$1)

Proof-of-personhood (Worldcoin) or social graph ZK proofs

Graph Portability

Vendor lock-in (30+ days)

Full portability (EIP-6551, ERC-6551)

Selective portability via ZK attestations

Monetization Vector

Extract attention, sell ads

Speculate on social tokens

Sell exclusive access, content, and influence

Primary Risk

Platform censorship, data breaches

Public harassment, financial griefing

ZK tech complexity, proof generation latency

deep-dive
THE IDENTITY STACK

Architecture of a Private Graph: zkLogin, Sismo, and the Compliance Layer

Private social graphs will win by decoupling identity verification from data exposure, enabling compliant, capital-efficient protocols.

Private graphs win with selective disclosure. The current Web3 model forces a binary choice: full doxxing or complete anonymity. Protocols like zkLogin (Sui) and Sismo invert this by using zero-knowledge proofs to verify credentials without revealing the underlying data. A user proves they are a US citizen without showing their passport.

The compliance layer is the moat. This architecture creates a permissioned data layer that protocols can query. A DeFi app can verify a user's accredited investor status via a zk-proof from Verite or KYC providers, enabling compliant on-chain private credit without exposing personal data. This solves the regulatory bottleneck.

Capital efficiency drives adoption. Private graphs enable soulbound reputation and under-collateralized lending. A user's proven, private history of on-chain repayments becomes a verifiable asset. This creates a trust graph more valuable than public transaction history, moving value from public ledgers to private attestations.

Evidence: The total value of compliance-driven DeFi (like Maple Finance's permissioned pools) exceeds $1.5B. Protocols integrating Sismo's ZK Badges have seen user onboarding increase by over 300%, as users selectively prove traits without linking wallets.

protocol-spotlight
SOCIAL GRAPH PRIMITIVES

Builders on the Frontier

The next bull run will be won by protocols that own the social layer, not just the financial one. Here are the primitives enabling private, composable, and user-owned social graphs.

01

Lens Protocol: The De Facto Social Graph

The Problem: Social platforms are walled gardens that lock user identity and relationships. The Solution: A decentralized, composable social graph where profiles are NFTs and interactions are portable assets.

  • Key Benefit: ~1M+ profiles minted, creating a foundational on-chain identity layer.
  • Key Benefit: Enables a permissionless ecosystem of hundreds of client apps (e.g., Orb, Phaver) built on a single graph.
1M+
Profiles
Polygon
Network
02

Farcaster Frames: The Distribution Hack

The Problem: DApps struggle with user acquisition and engagement outside of speculative finance. The Solution: Embeddable, interactive mini-apps inside social feeds that turn any cast into a transactional surface.

  • Key Benefit: Drove ~500% user growth for Farcaster by making social feeds actionable.
  • Key Benefit: Frames are permissionless distribution, bypassing App Store fees and gatekeepers.
500%
Growth Spike
0%
Platform Tax
03

Private Compute (e.g., Elusiv, Aztec): The Privacy Layer

The Problem: Fully public social graphs leak sensitive data, making mainstream adoption impossible. The Solution: Zero-knowledge proofs and private smart contracts that enable private interactions and subscriptions.

  • Key Benefit: Enables private social tokens & gated content without exposing subscriber lists.
  • Key Benefit: Decouples social activity from public financial history, reducing doxxing and harassment vectors.
ZK
Tech Stack
100%
Data Obfuscated
04

The Data Portability War

The Problem: Users cannot take their social capital (followers, posts, reputation) across platforms. The Solution: Open graph standards and data unions that let users own and monetize their social footprint.

  • Key Benefit: Breaks platform lock-in, forcing competition on user experience, not data moats.
  • Key Benefit: Creates new models for user-led data monetization, shifting value from corporations to individuals.
0
Lock-in
User-Owned
Revenue Model
counter-argument
THE MISPLACED BET

Counterpoint: "But Network Effects Are Everything"

Public social graphs are a legacy bet on a broken model; private graphs unlock superior monetization and user experience.

Network effects are not monolithic. The dominant narrative confuses public network effects—valuable for discovery—with private network effects, which drive actual utility and trust. Farcaster and Lens Protocol built public directories, but their most valuable interactions (DMs, group chats, commerce) require private, permissioned contexts.

Private graphs monetize better. Public feeds are ad-reliant and low-intent. A private social graph enables direct, high-value transactions—tipping, paid subscriptions, NFT-gated access—without platform rent extraction. This mirrors the shift from public Uniswap pools to private OTC desks in DeFi.

Data ownership changes the game. Users own their private graph connections as verifiable credentials or Soulbound Tokens. This portability destroys platform lock-in, the traditional source of network effect moats. Protocols like XMTP for private messaging demonstrate this shift.

Evidence: Farcaster's 'Frames' feature, which embeds interactive apps in casts, saw adoption spike not from the public timeline, but from private shares within trusted circles, proving utility flows through private channels first.

risk-analysis
THE DATA MONOPOLY TRAP

The Bear Case: Where This All Breaks

Public, on-chain social graphs are a noble experiment, but they fail the market test by ignoring fundamental user behavior and economic incentives.

01

The Sybil-Proof Identity Paradox

Public graphs require a unique, persistent identity to be valuable. On-chain, this is impossible without a centralized attestor. The result is Sybil spam and reputation dilution, rendering the graph useless for trust.\n- Lens Protocol and Farcaster rely on paid or permissioned sign-ups as a weak proxy.\n- Vitalik's 'Soulbound Tokens' remain a theoretical solution with no scalable, privacy-preserving implementation.

>90%
Spam Accounts
$0
Sybil Cost
02

The Privacy-First Network Effect

High-value social and professional interactions are inherently private. Public graphs capture only the lowest-common-denominator broadcast content, missing the real network value.\n- Platforms like Telegram and Signal dominate because encryption is the default.\n- Private graphs (e.g., Neynar, Karma3 Labs) can bootstrap via closed communities, guilds, and DAOs where trust is established off-chain first.

2B+
Encrypted Users
10x
Engagement Value
03

The Ad-Based Revenue Incompatibility

On-chain social platforms reject the surveillance capitalism model, destroying the $200B+ digital ad revenue pool. Without a proven alternative monetization model, they cannot compete for developer talent or user acquisition.\n- Farcaster's 'Frames' are a clever hack, not a sustainable economy.\n- Private graphs enable B2B SaaS models, selling analytics and reputation scores to protocols like Aave, Compound, and Uniswap for underwriting.

$0
Ad Revenue
$10K+
SaaS ARPU
04

The UX Friction of Sovereign Data

Giving users true ownership means they bear the cost and complexity of key management, storage, and portability. 99% of users will delegate this back to a custodian, recreating the platform monopoly.\n- See the failure of Solid (Tim Berners-Lee's decentralized web project).\n- Private graph providers like Spindl or Goldsky abstract this away, offering a clean API while cryptographically proving data integrity.

<1%
Self-Custody
~500ms
API Latency
05

The Interoperability Mirage

The promise of composable social graphs across apps is broken by niche data schemas and zero monetization for data creators. Why would Friend.tech share its valuable graph with a competitor?\n- Cross-chain social via LayerZero or Axelar just moves the silo problem.\n- Private graphs win by being vertical-specific (DeFi, gaming, research) and selling access, not by pursuing universal standards.

0
Shared Schemas
100%
Walled Gardens
06

The Venture Capital Reality

VCs need $1B+ exit potential. Public social graphs have no clear path to this scale without becoming the advertising giants they seek to replace. The capital will flow to infrastructure plays with enterprise contracts.\n- Look at the funding for Espresso Systems (privacy infra) vs. consumer social dapps.\n- The winners will be the AWS of social data, not the next Facebook.

100:1
Infra vs. DApp Funding
B2B
Revenue Model
future-outlook
THE SOCIAL GRAPH

The 2025 Landscape: Loyalty, Credit, and On-Chain Reputation

Private, user-owned social graphs will become the foundational primitive for the next generation of on-chain applications.

Private social graphs win because they invert the data ownership model. Platforms like Farcaster and Lens Protocol give users cryptographic control over their network, turning followers and interactions into portable assets. This creates a durable moat that public, on-chain graphs cannot replicate.

Reputation becomes undercollateralized credit. A verified, multi-chain history of reliable interactions on Ethereum or Solana acts as a Soulbound Token of trust. Protocols like Goldfinch and Maple will use this to price risk for loans without requiring overcollateralization, unlocking trillions in latent capital.

Loyalty programs become interoperable. A Starbucks stamp on Base and an airline mile on Avalanche exist in the same wallet. Private graphs enable cross-brand loyalty aggregation, turning fragmented points into a composite reputation score that dictates real-world benefits and access.

takeaways
THE DATA MOAT THESIS

TL;DR for Builders and Investors

The next bull run will be defined by applications that own their user relationships, not their infrastructure. Private social graphs are the defensible asset.

01

The Problem: The Ad-Surveillance Model is Terminal

Web2 social platforms treat user connections as proprietary data to be mined. This creates:\n- Vendor lock-in and platform risk (e.g., API changes, de-platforming)\n- Incentive misalignment: User growth fuels the platform's ad revenue, not the user's network value\n- Fragmented identity: Your graph is siloed on Twitter, LinkedIn, Farcaster—never truly yours

>90%
Ad Revenue Share
$0
User Payout
02

The Solution: Portable, Sovereign Graphs

On-chain social graphs (e.g., Farcaster, Lens Protocol) decouple social data from applications.\n- User-owned keys = control over connections and content\n- Composability: A single graph can power infinite apps, from feeds to marketplaces\n- Monetization shifts: Value accrues to graph participants via direct tipping, NFT sales, and community tokens

1
Graph, Many Clients
100%
Portable
03

The Catalyst: Farcaster Frames & On-Chain Context

Frames turn any cast into an interactive app, demonstrating the power of a composable graph. This is the killer use-case for builders.\n- Instant distribution: Embed commerce, voting, minting directly into the feed\n- Rich context: Apps can read a user's verifiable on-chain history (POAPs, tokens, DAO votes) to personalize experiences\n- New business models: Transaction-fee revenue from in-feed actions, not ads

10x
Engagement Lift
<2s
Tx Time
04

The Investment Lens: Infrastructure > Apps

Bet on the picks and shovels. The winning apps will be built on top of decentralized social graphs.\n- Indexing & Query Layers (e.g., The Graph, Goldsky): Critical for performant social feeds\n- ZK Privacy Layers (e.g., Aztec, Polygon Miden): Enable private social interactions and voting\n- Data Network Effects: The graph with the most valuable, active users becomes the liquidity pool for attention

L1/L2
Protocol Value
App
Execution Risk
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Why Private Social Graphs Will Win the Next Bull Run | ChainScore Blog