In 1971, psychologist and economist Herbert A. Simon introduced the concept of attention economy, arguing that in an era of information overload, human attention has become the most scarce resource. This idea has only grown more relevant in today’s digital landscape.
Albert Wenger, economist and managing partner at USV, expanded on this in The World After Capital, describing a pivotal shift in human civilization: from the industrial age’s capital scarcity to the knowledge age’s attention scarcity.
- Agricultural Revolution: solved food scarcity, but sparked land competition
- Industrial Revolution: solved land scarcity, leading to resource and capital accumulation
- Digital Revolution: now revolves around attention
This transformation is driven by two key traits of digital technology: near-zero marginal cost of information replication and the ubiquity of AI computing—while human attention remains finite and non-replicable.
From Labubu's viral success in the collectibles market to top streamers dominating live commerce, the core battle is for user attention. Yet in traditional attention economies, users—who generate data and engagement—are rarely rewarded. Instead, platforms and intermediaries capture most of the value.
Enter InfoFi (Information + Finance), a Web3 innovation leveraging blockchain, token incentives, and AI to democratize information value. By making information production, distribution, and consumption transparent and rewarding contributors directly, InfoFi aims to rebalance the scales.
This article explores the categories of InfoFi, its challenges, and emerging trends shaping its future.
What Is InfoFi?
InfoFi merges information and finance, transforming abstract, hard-to-measure concepts—like attention, reputation, insights, and narrative momentum—into quantifiable, tradable digital assets. It goes beyond traditional prediction markets to include social influence, user-generated intelligence, and real-time sentiment tracking.
Key Advantages of InfoFi
- Value Redistribution: Returns economic value to actual contributors—creators, sharers, validators—via smart contracts and token incentives.
- Information Monetization: Turns intangible assets (e.g., attention, insight) into tradeable tokens.
- Low-Barrier Participation: Users can join with just a social media account.
- Multi-Layer Incentives: Rewards not just creation, but also sharing, engagement, and verification—supporting long-tail contributors.
- AI-Powered Enhancement: Integrates AI for content quality assessment, prediction accuracy, and market efficiency.
Categories of InfoFi
Prediction Markets
Prediction markets use collective intelligence to forecast future events—from elections to product launches. Participants buy shares tied to outcomes; market prices reflect group expectations. These aren’t just gambling tools—they’re mechanisms for surfacing truth through financial incentives.
Vitalik Buterin has long championed prediction markets. In his 2024 essay "From Prediction Markets to Info Finance," he described them as tools with transformative potential across media, science, and governance. He noted Polymarket’s dual nature: a betting site for users, a real-time news source for observers.
Elon Musk echoed this sentiment before the 2024 U.S. election, sharing Polymarket data showing Trump leading 51%, stating: “With real money on the line, this is more accurate than polls.”
Leading Platforms
- Polymarket: Built on Polygon, uses USDC. Users predict outcomes on politics, economics, entertainment, and tech.
- Kalshi: CFTC-regulated in the U.S., accepts crypto deposits (USDC, BTC, SOL, etc.) but settles in fiat. Focuses on event contracts with strong compliance advantages.
👉 Discover how decentralized prediction markets are reshaping truth discovery
Yap-to-Earn (a.k.a. "Mouth Mining")
“Yap-to-Earn” is a playful term for earning tokens by sharing insights on social platforms—especially X (Twitter). Unlike traditional Web3 actions (staking, trading), it rewards information contribution.
AI algorithms assess content quality, depth, engagement, and originality to distribute points or future token airdrops.
Key Features
- No capital or on-chain activity required
- Encourages meaningful discussion
- AI filters bots and spam
- Points can convert into tokens or privileges
Notable Projects
- Kaito AI: The leading Yap-to-Earn platform. Evaluates crypto-related posts on X using AI. Has distributed over $90 million in token value (excluding its own airdrop), with 200k+ monthly active users.
- Cookie.fun: Tracks “mindshare” of AI agents and projects. Rewards creators via Snaps for contributing to project visibility.
- Virtuals: An AI agent launchpad that incorporates Yap-to-Earn via Kaito for its Genesis Launch on Base.
- Loud: Gained 70%+ share on Kaito’s attention leaderboard pre-launch. Post-launch fees are distributed to top 25 attention earners.
- Wallchain Quacks: On Solana, uses custom LLMs to reward insightful content daily.
Multi-Dimensional Contribution Models
Some platforms combine content creation with on-chain actions or tasks to assess holistic user value.
- Galxe Starboard: Rewards both off-chain (social posts) and on-chain actions (dApp interaction, NFT minting). Measures impact via engagement, sentiment, virality.
- Mirra: A decentralized AI model trained on community-curated Web3 content. Users submit insights by tagging @MirraTerminal; “Scouts” help shape AI learning.
Reputation-Based InfoFi
Reputation is a powerful but under-monetized asset. These protocols tokenize credibility.
- Ethos: Generates a Credibility Score using Social Proof-of-Stake (Social PoS). Based on comments, endorsements (staking ETH to back others), and open protocols. Offers a reputation marketplace where users can speculate on others’ trustworthiness.
- GiveRep: Built on Sui. Converts X activity into chain-based reputation. Daily comment limits prevent spam; Sui ecosystem participants earn bonus points.
Attention & Trend Markets
These platforms let users bet on or profit from attention trends.
- Noise: On MegaETH, allows users to go long or short on project attention (invite-only).
- Upside: A social prediction market (backed by Arthur Hayes). Rewards content discovery via upvotes. Final 5-minute vote weight decay prevents manipulation.
- YAPYO: Arbitrum-based infrastructure turning attention into lasting influence.
- Trends: Tokenizes X posts via bonding curves. Creators earn 20% of trading fees per trend.
Token-Gated Content Access
Filters noise by requiring ownership of a token to access premium content.
- Backroom: Creators launch token-gated spaces for alpha and analysis. Access keys are tradable assets with dynamic pricing.
- Xeet: On Abstract Network (in development). Will integrate Ethos scores. Founder @Pons_ETH critiques current InfoFi as “NoiseFi,” advocating for signal enhancement.
Data Intelligence Platforms
- Arkham Intel Exchange: A decentralized intelligence marketplace where “on-chain detectives” earn bounties by uncovering insights.
Challenges Facing InfoFi
Prediction Markets
- Regulatory Risk: Polymarket was fined $1.4M by CFTC in 2022 for operating without registration. U.S. legal scrutiny remains high.
- Insider Influence & Manipulation: Large players may distort prices; fair mechanisms are crucial.
- Liquidity Gaps: Niche topics suffer from low participation. AI agents may help but aren’t a full fix.
- Oracle Vulnerabilities: Polymarket suffered oracle attacks. UMA, Polymarket, and EigenLayer are now collaborating on secure oracle designs with AI integration and anti-bribery features.
Yap-to-Earn Issues
- Noise Overload: Flood of AI-generated spam drowns real insights. Projects complain about low ROI despite high spending.
- Opaque Algorithms: Lack of transparency in scoring fuels distrust. Kaito recently updated its system to prioritize quality over quantity and penalize manipulation.
- Wealth Concentration: Top creators dominate rewards. Only ~3% of Kaito’s 1M users have earned points.
- Short-Lived Engagement: Attention spikes then collapses post-airdrop (e.g., LOUD’s market cap dropped from $30M to <$600K).
- Attention ≠ Value: High visibility doesn’t guarantee long-term success.
Reputation Systems
- High Entry Barriers: Invite-only models like Ethos limit growth.
- Sybil & Manipulation Risks: Fake identities threaten integrity.
- Fragmentation: No cross-platform score compatibility—data silos persist.
Emerging Trends in InfoFi
AI + Prediction Markets
AI enhances forecasting by analyzing vast datasets and simulating outcomes. It may also deploy autonomous agents to solve long-tail liquidity issues.
👉 See how AI agents are transforming market prediction accuracy
Social + Prediction Integration
X’s June 2025 partnership with Polymarket marks a turning point. By combining Grok’s analytics with real-time X data, users gain instant, context-rich insights—potentially making prediction markets a core layer of future information infrastructure.
Futarchy & Governance
Vitalik supports Futarchy—a governance model where “vote on values, bet on beliefs.” Communities set success metrics; prediction markets decide policy effectiveness. This data-driven approach reduces bias and rhetoric in decision-making.
Evolution of Yap-to-Earn + Reputation
Future developments include:
- Semantic analysis for better content valuation
- Incentives for long-tail creators
- Penalty systems for spam
- Web3-native LLMs trained on high-quality data
- Cross-platform expansion beyond X
- Integration with news outlets for broader adoption
Reputation scores could soon underpin DeFi lending and staking—acting as creditworthiness indicators.
Data + Creator Insights Fusion
Next-gen platforms will merge analytics dashboards with AI interpretation—and reward users for contributing insights or distributing valuable data.
👉 Explore how tokenized attention is redefining digital influence
Conclusion: The Path Forward for InfoFi
The core tension of the digital age is clear: those who create attention rarely capture its value. InfoFi seeks to correct this imbalance by tokenizing information flows and redistributing value fairly.
But success hinges on balancing three pillars:
- Information discovery
- User participation
- Value return
Without thoughtful mechanism design, InfoFi risks repeating SocialFi’s boom-and-bust cycle—dominated by speculation over substance.
The goal isn’t just to monetize attention, but to build a more transparent, equitable knowledge economy. With AI amplification and blockchain accountability, Web3 has the tools to make it happen—if it prioritizes inclusivity over extraction.
The future of information isn’t just about who speaks loudest—it’s about who contributes meaningfully.
Frequently Asked Questions (FAQ)
Q: What is InfoFi?
A: InfoFi (Information + Finance) uses blockchain and token incentives to turn abstract information—like attention, reputation, or insights—into measurable, tradable assets.
Q: How does Yap-to-Earn work?
A: Users earn points or tokens by posting insightful content on social platforms like X. AI evaluates quality, engagement, and depth to distribute rewards.
Q: Are prediction markets legal?
A: It depends on jurisdiction. Platforms like Kalshi comply with U.S. regulations (CFTC), while others like Polymarket face restrictions due to unregistered operations.
Q: Can reputation be tokenized?
A: Yes—projects like Ethos and GiveRep convert social credibility into quantifiable scores using on-chain and social data.
Q: Why is AI important in InfoFi?
A: AI improves content evaluation, detects spam, enhances prediction accuracy, and enables autonomous agents to boost market efficiency.
Q: Is InfoFi just hype or does it have real utility?
A: While speculative activity exists, InfoFi enables real use cases—better forecasting, fairer creator rewards, decentralized intelligence markets—and could reshape how we value information online.
Core Keywords: InfoFi, prediction markets, Yap-to-Earn, tokenized attention, Web3 finance, AI in blockchain, decentralized reputation