InfoFi: The Attention Economy Revolution in the Web3 Era

In 1971, psychologist and economist Herbert Simon first proposed the theory of attention economy, pointing out that in a world of information overload, human attention has become the scarcest resource.

Economist and USV managing partner Albert Wenger further reveals a fundamental shift in "The World After Capital": human civilization is undergoing a third leap - from the "capital scarcity" of the industrial age to the "attention scarcity" of the knowledge age.

• Agricultural Revolution: Aimed at solving food scarcity issues, but led to land disputes;
• Industrial Revolution: Aimed at solving the problem of land scarcity, but shifted towards resource competition and capital accumulation;
• Digital Revolution: The Battle for Attention.

The underlying driving force of this transformation stems from two key characteristics of digital technology: the zero marginal cost of information replication and dissemination, and the universality of AI computation (although human attention is non-replicable).

Whether it is the booming潮玩 market or the live streaming sales by top anchors, it is essentially a competition for the attention of users and viewers. However, in the traditional attention economy, users, fans, and consumers contribute their attention as "data fuel," while the excess profits are monopolized by platforms and scalpers. The InfoFi in the Web3 world attempts to overturn this model—using blockchain, token incentives, and AI technology to make the production, dissemination, and consumption of information transparent, aiming to return value to the participants.

This article will provide an in-depth introduction to the classification of the InfoFi project, the challenges it faces, and future development trends.

What is InfoFi?

InfoFi is a combination of Information and Finance, focusing on transforming hard-to-quantify and abstract information into dynamic and quantifiable value carriers. This encompasses not only traditional prediction markets but also the distribution, speculation, or trading of information or abstract concepts such as attention, reputation, on-chain data or intelligence, personal insights, and narrative activity.

The core advantages of InfoFi are reflected in:

• Value Redistribution Mechanism: Returning the value monopolized by platforms in the traditional attention economy to the true contributors. Through smart contracts and incentive mechanisms, enabling information producers, disseminators, and consumers to share in the profits.
• Information monetization capability: Transforming abstract elements such as attention, insights, reputation, and narrative activity into tradable digital assets, thereby creating a trading market for the previously hard-to-circulate value of information.
• Low threshold participation: Users can participate in value distribution through content creation using only their social media accounts.
• Innovation of incentive mechanisms: not only rewarding content creation but also including various aspects such as dissemination, interaction, and verification, allowing niche content and long-tail users to also receive rewards. High-quality content receives more rewards, encouraging the continuous production of high-quality information;
• Cross-domain application potential: For example, the introduction of AI provides InfoFi with advantages such as content quality assessment and market optimization prediction.

InfoFi Classification

InfoFi covers various different application scenarios and models, which can mainly be divided into the following categories:

prediction market

Prediction markets, as a core component of InfoFi, are a mechanism for forecasting future event outcomes through collective intelligence. Participants express their expectations about future events (such as election or policy outcomes, sports events, economic forecasts, price expectations, product release dates, etc.) by buying and selling ‘shares’ linked to specific event outcomes, and the market prices reflect the collective expectations of the crowd regarding the event outcomes. Polymarket is a representative application promoting the concept of InfoFi.

Vitalik has always been a loyal supporter of the prediction market Polymarket. In his article "From Prediction Markets to Information Finance" published in November 2024, he stated, "Prediction markets have the potential to create better applications in social media, science, news, governance, and other areas. I call such markets information finance." Vitalik also pointed out the dual nature of Polymarket: one is a gambling site for participants, and the other is a news site for everyone else.

Under the framework of InfoFi, prediction markets are not merely tools for speculation, but platforms for uncovering and revealing real information through financial incentives. This mechanism leverages market efficiency, encouraging participants to provide accurate information, as correct predictions yield economic returns, while incorrect predictions may lead to losses. Musk himself retweeted data stating "Trump leads with 51% support on Polymarket" a month before the 2024 U.S. election, commenting: "Due to the involvement of real monetary stakes, this data is more accurate than traditional polls."

Prediction market representative platforms include:

• Polymarket: The largest decentralized prediction market, Polymarket is built on the Polygon network and uses USDC stablecoin as the trading medium. Users can make predictions on events such as political elections, economy, entertainment, and product launches.
• Kalshi: It is a fully CFTC-regulated prediction market platform in the United States that supports deposits in USDC, BTC, WLD, SOL, XRP, and RLUSD through collaboration with the cryptocurrency and stablecoin infrastructure provider Zero Hash, but settles in fiat currency. Kalshi focuses on Event Contracts, allowing users to trade the outcomes of political, economic, and financial events. Due to regulatory compliance, Kalshi has a unique advantage in the U.S. market.

Mouth Licking Type InfoFi (Yap-to-Earn)

"Yap-to-Earn" is a colloquial term in the Chinese crypto community, referring to earning rewards by sharing insights and content. The core concept of Yap-to-Earn is to encourage users to post high-quality, crypto-related posts or comments on social platforms, primarily evaluated by AI algorithms based on the quantity, quality, engagement, and depth of the content, thereby distributing points or token rewards. This model differs from traditional on-chain activities (such as trading or staking) as it places greater emphasis on users' contributions and influence within the community.

Features of "Zui Lu":

• No on-chain transactions or large capital required, just an X account is needed to participate.
• Enhance the activity of the project community by rewarding valuable discussions.
• AI algorithms reduce human intervention, filter out bots and low-quality content, ensuring a more transparent reward distribution.
• Points may be converted into token airdrops or ecological privileges, with early participants potentially receiving higher returns.

Current mainstream mouth-licking projects or projects that support mouth-licking include:

Kaito AI: is a representative platform for Yap-to-Earn, which has collaborated with multiple projects to evaluate the quantity, quality, interactivity, and depth of user-generated crypto-related content published on X through AI algorithms, rewarding Yap points for users to compete for leaderboard placements to earn token airdrops.

In this way, creators can not only effectively prove their influence and content value through Yaps, but also attract precise high-quality attention; ordinary users can efficiently discover quality content and KOLs through the Yaps system; and project parties achieve the dual goals of precisely reaching target users and expanding brand influence, forming a virtuous ecological cycle of mutual benefit.

Kaito AI has distributed tokens worth over $90 million to various communities (excluding Kaito's own airdrops), with more than 200,000 active Yappers each month.

Cookie.fun: Cookie tracks the mindshare, interaction, and on-chain data of AI agents, generating a comprehensive market overview, while also tracking the mindshare and sentiment of cryptocurrency projects. The Cookie Snaps system includes a built-in rewards and airdrop activity system to reward Cookie creators who contribute to project attention.

Cookie has collaborated with three projects to launch the Snaps event, namely Spark, Sapien, and OpenLedger. Among them, the number of participants in the Spark event exceeded 16,000, while the participation numbers for the latter two projects were 7,930 and 6,810 respectively.

Virtuals: Virtuals itself is not a platform focused on Yap-to-Earn, but rather an AI agent launch platform. However, in mid-April, it launched a new launch mechanism called Genesis Launch on Base, and one of the ways to earn points for participation in the launch includes Yap-to-Earn (supported by Kaito).

Loud: As a "Attention Value Experiment" within the Kaito AI ecosystem, Loud captured more than 70% of the Kaito attention leaderboard through the Yap-to-Earn activity before the official release of its token via Initial Attention Offering (IAO) at the end of May 2025. The LOUD operating mechanism is also centered around the "Attention Economy," where transaction fees collected after the market opens are primarily distributed in the form of SOL to the top 25 users on the attention leaderboard.

Wallchain Quacks: Wallchain is a programmatic AttentionFi project based on Solana, supported by AllianceDAO. Wallchain X Score evaluates the overall influence of users, while Wallchain Quacks rewards high-quality content and valuable interactions. Currently, the Wallchain Quacks custom LLM assesses creator content daily, and creators of valuable, insightful content will receive Quacks rewards.

Mouth Lick + Tasks / On-chain Activities / Verification: Multi-dimensional Contribution Valuation

Some projects also assess users' multidimensional contributions by combining content contributions with on-chain behaviors (such as trading, staking, and NFT minting) or tasks.

Galxe Starboard: Galxe is a Web3 growth platform, and its newly launched Galxe Starboard is dedicated to rewarding real contributions in off-chain and on-chain actions. Projects can define multiple contribution tiers, where what's important is not just how many tweets have been sent, but the value brought to the entire project, including post engagement, sentiment, virality, interaction with dApps, token holding, minting NFTs, or completing on-chain tasks.

Mirra: Mirra is a decentralized AI model trained on community-selected data, capable of learning from real-time contributions of Web3 users. Specifically, creators publish high-quality content on X, which is equivalent to submitting AI validation data; scouts identify high-value content on X and tag @MirraTerminal in replies to submit insights, determining what content the AI learns from, helping to shape an intelligent AI.

Reputation-based InfoFi

Ethos is an on-chain reputation protocol that is fully based on open protocols and on-chain records, combined with Social Proof of Stake (Social PoS), to generate credibility scores through decentralized mechanisms, ensuring the reliability, decentralization, and Sybil resistance of its reputation system. Currently, Ethos adopts a strict invitation-only system. The core function of Ethos is to generate credibility scores, a quantifiable metric of user trust on the chain. The scores are based on the following on-chain activities and social interactions: a commenting mechanism (with cumulative utility) and a guarantee mechanism (staking Ethereum to endorse other users).

Ethos also launched a reputation market, allowing users to speculate on the reputation of individuals, companies, DAOs, and even AI entities by buying and selling "trust tokens" and "distrust tokens," essentially going long or short on reputation.

GiveRep: Built primarily on Sui, it aims to transform users' social influence and community participation on the X platform into quantifiable on-chain reputation through their activities, incentivizing user participation through rewards. Commenting under a creator's post and mentioning the official GiveRep Twitter will grant both the commenter and the creator one reputation point each. To limit abusive behavior, GiveRep restricts users to a maximum of 3 such comment mentions per day (including 3), while creators can receive unlimited points daily. Mentions from Sui ecosystem projects and ambassadors will earn more points.

Attention Market / Prediction

Noise: is a trend discovery and trading platform based on MegaETH, currently requiring an invitation code for access. Users can long or short the project's attention.

Upside: Upside is a