A Complete Interpretation of the InfoFi Ecosystem: An Attention Market Empowered by AI, or a New Scythe for Playing Retail Investors for Suckers?

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 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: Competing for Attention.

The underlying driving force of this transformation stems from two major characteristics of digital technology: the zero marginal cost of information replication and dissemination, and the universality of AI computation (though human attention is not replicable).

Whether it is the popularity of Labubu in the trendy toy market or the live streaming sales of top influencers, they essentially compete for the attention of users and viewers. However, in the traditional attention economy, users, fans, and consumers contribute attention as "data fuel", while excess profits are monopolized by platforms and scalpers. The InfoFi in the Web3 world attempts to overturn this model—by using blockchain, token incentives, and AI technology to make the processes of information production, dissemination, and consumption 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 the future development trends.

What is InfoFi?

InfoFi is a combination of Information + Finance, with the core focus on transforming difficult-to-quantify and abstract information into dynamic and quantifiable value carriers. This not only encompasses traditional prediction markets but also includes 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: Return the value monopolized by platforms in the traditional attention economy to the real contributors. Through smart contracts and incentive mechanisms, allow information producers, disseminators, and consumers to share the profits.
• Information Value-Added Capability: Transforming abstract attention, insights, reputation, narrative activity, etc. into tradable digital assets, creating a trading market for the value of information that is originally difficult to circulate.
• Low threshold for participation: Users can participate in value distribution through content creation with just a social media account.
• Innovation of incentive mechanisms: It not only rewards content creation but also includes multiple aspects such as dissemination, interaction, and verification, allowing niche content and long-tail users to also receive rewards. High-quality content receives more rewards, incentivizing 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.

InfoFi Classification

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

prediction market

Prediction markets, as a core component of InfoFi, are a mechanism for predicting future event outcomes through collective intelligence. Participants express their expectations for future events (such as election or policy outcomes, sports events, economic forecasts, price expectations, product release times, etc.) by buying and selling "shares" linked to specific event outcomes, with the market price reflecting the collective expectations of the group regarding the event outcome. Polymarket is a representative application promoting the concept of InfoFi.

Under the framework of InfoFi, prediction markets are not just tools for speculation, but platforms that uncover and reveal real information through financial incentives. This mechanism leverages market efficiency, encouraging participants to provide accurate information, as correct predictions yield economic rewards, while incorrect predictions may lead to losses. Elon Musk himself retweeted data stating "Trump leads with a 51% approval rating on Polymarket" a month before the 2024 US election, commenting, "Due to real monetary stakes involved, this data is more accurate than traditional polls."

The representative platforms for prediction markets include:

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

Mouth Lick Type InfoFi (Yap-to-Earn)

"Yap-to-Earn" is a colloquial term in the Chinese crypto community, referring to earning rewards through 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, interaction, and depth of content, thus distributing points or token rewards. This model differs from traditional on-chain activities (like trading or staking) and places greater emphasis on users' information contributions and influence within the community.

Characteristics of "mouth play":

• No on-chain transactions or large capital required, you only need an X account 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, and early participants may receive higher returns.

Current mainstream mouth-operated projects or projects that support mouth operation include:

Kaito AI: is a representative platform of Yap-to-Earn, which has collaborated with multiple projects to assess 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 on the leaderboard 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; while project parties achieve the dual goals of precisely reaching target users and expanding brand influence, forming a virtuous ecological cycle of mutual benefit for multiple parties.

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

Cookie.fun: Cookie tracks the mindshare, interaction status, and on-chain data of AI agents, generating a comprehensive market overview, while also tracking the mindshare and sentiment of crypto projects. The Cookie Snaps system includes a rewards and airdrop activity system, providing rewards to 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 number of participants in the latter two projects was 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 release mechanism called Genesis Launch on Base. One of the ways to earn points required for participation in the launch includes Yap-to-Earn (supported by Kaito).

Loud: As a "attention value experiment" within the Kaito AI ecosystem, Loud once occupied more than 70% of the Kaito attention leaderboard through the Yap-to-Earn activity before officially launching its token via the Initial Attention Offering (IAO) at the end of May 2025. The LOUD operating mechanism also revolves around the "attention economy", where the transaction fees collected after trading is opened are mainly distributed in 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, Wallchain Quacks' custom LLM evaluates creators' content daily, and valuable, insightful content creators will receive Quacks rewards.

Mouth Licking + Tasks / On-chain Activities / Verification: Multi-dimensional Contribution Value Realization

Some projects also combine content contributions with on-chain activities (such as trading, staking, NFT minting) or tasks to comprehensively evaluate users' multidimensional contributions.

Galxe Starboard: Galxe is a Web3 growth platform, and its newly launched Galxe Starboard aims to reward genuine contributions in off-chain and on-chain actions. Projects can define multiple layers of contribution, where it's not just about how many tweets were sent, but the value brought to the entire project, including post engagement, sentiment, virality, interaction with dApps, holding tokens, minting NFTs, or completing on-chain tasks.

Mirra: Mirra is a decentralized AI model trained on community-selected data, capable of learning from the 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 and helping to shape intelligent AI.

Reputation-based InfoFi

Ethos is an on-chain reputation protocol that is entirely based on open protocols and on-chain records, combined with Social Proof of Stake (Social PoS). It generates a Credibility Score through decentralized mechanisms, ensuring the reliability, decentralization, and Sybil resistance of its reputation system. Currently, Ethos adopts a strict invitation system. The core function of Ethos is to generate a Credibility Score, a quantifiable indicator of user trustworthiness on-chain. The score is based on the following on-chain activities and social interactions: a commenting mechanism (with cumulative utility) and a guarantor mechanism (staking Ethereum to back other users).

Ethos also launched a reputation market that allows users to speculate on the reputation of individuals, companies, DAOs, and even AI entities by buying and selling "trust votes" and "distrust votes," allowing for long or short positions on reputation.

GiveRep: Built primarily on Sui, it aims to convert users' social influence and community participation on platform X into quantifiable on-chain reputation through user activities, incentivizing participation through rewards. Commenting and mentioning the official GiveRep Twitter under the creator's post allows both the commenter and the creator to earn one reputation point each. To limit abuse, GiveRep restricts users to a maximum of 3 such mention comments 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 to experience. Users can go long or short on the project's attention.

Upside: Upside is a social prediction market (investors include Arthur Hayes) that rewards the discovery, sharing, and prediction of valuable content and links, creating a dynamic market through a liking mechanism. Earnings are distributed proportionally to voters, creators, and curators. To prevent manipulation of the prediction pool, the weight of likes is reduced in the last 5 minutes of each round.

YAPYO: An attention market infrastructure within the Arbitrum ecosystem. YAPYO states that the rewards in its coordination mechanism are not just profits, but also lasting influence.

Trends: Tokens can be used to tokenize X posts, becoming a trend on the joint curve called "Trend it." Creators are eligible to receive 20% of the joint curve trading fees for each trend.

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