The Light and Shadow of InfoFi: Where is the Road to Breakthrough in the Ecological Panorama?

InfoFi prisoner's dilemma: The game dilemma of profit distribution under the Matthew effect between information mining and noise vortex.

Author: KarenZ, Foresight News

In 1971, psychologist and economist Herbert A. Simon first proposed the attention economy theory, 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 the problem of food scarcity, but giving rise to land disputes;
• Industrial Revolution: aimed at solving the problem of scarce land, but turned to 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 (but human attention cannot be replicated).

Whether it's the popularity of Labubu in the trendy market, top anchors' live streaming sales, fundamentally, it is largely a competition for the attention of users and viewers. However, in the traditional attention economy, users, fans, and consumers contribute attention as 'data fuel', but the excess profits are monopolized by platforms, scalpers, and others. InfoFi in the Web3 world attempts to disrupt this model—by using blockchain, token incentives, and AI technology to make the process of information production, dissemination, and consumption transparent, aiming to return value to the participants.

This article will delve into the classification, challenges, and future development trends of the InfoFi project.

What is InfoFi?

InfoFi is a combination of Information + Finance, the core of which is to transform difficult-to-quantify, abstract information into dynamic, 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, narrative activity, etc.

InfoFi's core advantage lies in:

• Value redistribution mechanism: returning the value monopolized by platforms in the traditional attention economy to the true contributors. By using smart contracts and incentive mechanisms, information producers, disseminators, and consumers can share profits.
• Information valorization capability: transforming abstract attention, insights, reputation, narrative activity, etc. into tradable digital assets, creating a trading market for information value that was originally difficult to circulate.
• Low threshold participation: Users can participate in value distribution through content creation with just a social media account.
• Innovation of incentive mechanism: It rewards not only content creation but also dissemination, interaction, verification, and other aspects, enabling niche content and long-tail users to 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 advantages such as content quality evaluation and market optimization for InfoFi.

InfoFi Category

InfoFi covers a variety of different application scenarios and modes, mainly divided into the following categories:

Market Prediction

As a core component of InfoFi, the prediction market is a mechanism for predicting the outcome of future events through collective intelligence. Participants express their expectations for future events (such as election or policy results, sports events, economic forecasts, price expectations, product release timing, etc.) by buying and selling 'shares' linked to specific event outcomes, and the market price reflects the collective expectations of the community for the event outcome. 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 info finance" in November 2024, he stated that "prediction markets have the potential to create better applications in social media, science, news, governance, and other fields. I call these markets info finance." Vitalik also pointed out the dual nature of Polymarket: one as a betting site for participants and the other as a news site for everyone else.

Within the framework of InfoFi, the prediction market is not just a tool for speculation, but a platform for mining and revealing real information through financial incentive mechanisms. This mechanism leverages the efficiency of the market, encouraging participants to provide accurate information, as correct predictions can bring economic rewards, while incorrect predictions may lead to losses. Musk himself once retweeted data from 'Polymarket' a month before the 2024 US election, showing Trump leading with 51% support, and commented: 'Due to the real money involved, 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, with USDC stablecoin as the trading medium. Users can predict events such as political elections, economy, entertainment, product launches, etc.
• Kalshi: A prediction market platform in the United States that is fully regulated by the CFTC. Through a partnership with Zero Hash, a provider of cryptocurrency and stablecoin infrastructure, Kalshi supports deposits in USDC, BTC, WLD, SOL, XRP, and RLUSD, 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-Rubbing Type InfoFi (Yap-to-Earn)

"Mouth rubbing" is a humorous term used in the Chinese crypto community to refer to Yap-to-Earn, which involves earning rewards by sharing opinions and content. The core idea of Yap-to-Earn is to encourage users to post high-quality, crypto-related posts or comments on social platforms, and the content is mostly evaluated by AI algorithms based on quantity, quality, interaction, and depth, in order to allocate points or token rewards. This model differs from traditional on-chain activities, such as trading or staking, and places more emphasis on users' information contribution and influence within the community.

Features of "Mouth Stroke":

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

Current mainstream projects that support '嘴撸' or are supported by '嘴撸' include:

Kaito AI: It is the representative platform of Yap-to-Earn, has cooperated with multiple projects, evaluates the quantity, quality, interactivity, and depth of users' crypto-related content published on X through AI algorithms, rewards Yap points, and provides users with token airdrops to compete on the leaderboard.

In this way, creators can effectively demonstrate their influence and content value through Yaps, attracting precise and high-quality attention; ordinary users can efficiently discover high-quality content and KOL through the Yaps system; while the project party achieves the dual goals of reaching target users accurately and expanding brand influence, forming a win-win benign ecological cycle.

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

*Source:

Cookie.fun: Cookie tracks the mindshare, interaction, and on-chain data of AI agents, generates a comprehensive market overview, and also tracks the mindshare and emotions of encrypted projects. Cookie Snaps has a built-in reward and airdrop system, providing rewards for Cookie creators who contribute to project attention.

Cookie collaborated with three projects to launch the Snaps campaign, namely Spark, Sapien, and OpenLedger. Among them, the number of participants in the Spark campaign exceeded 16,000, while the number of participants in the latter two projects were 7930 and 6810, respectively.

Virtuals：Virtuals itself is not a platform dedicated to Yap-to-Earn, but an AI agent launch platform. However, in mid-April, a new launch mechanism Genesis Launch was introduced on Base, and one of the ways to earn points to participate in the launch includes Yap-to-Earn (supported by Kaito).

*Virtuals Among the top AI agent projects with high subscription rates, source:

Loud：As a part of the 'Attention Value Experiment' in the Kaito AI ecosystem, Loud once occupied over 70% of the Kaito attention leaderboard through Yap-to-Earn activities before the official token release through Initial Attention Offering (IAO) by the end of May 2025. The operation mechanism of LOUD also revolves around the 'attention economy', with the majority of the transaction fees collected after opening for trading being allocated in SOL form to the top 25 users in the attention leaderboard.

Wallchain Quacks: Wallchain is a Solana-based programmable AttentionFi project that is supported by AllianceDAO. Wallchain X Score evaluates users' overall influence, while Wallchain Quacks rewards high-quality content and valuable interactions. Currently, Wallchain Quacks customizes LLM to evaluate creators' content daily, and creators with valuable and insightful content will receive Quacks rewards.

Mouth roll + task / on-chain activities / verification: multi-dimensional value contribution

Some projects also evaluate users' multidimensional contributions by combining content contributions with on-chain activities (such as transactions, staking, NFT minting), or tasks.

Galxe Starboard：Galxe is a Web3 growth platform, and its latest release, Galxe Starboard, is dedicated to rewarding real contributions in both on-chain and off-chain actions. The project can define multiple layers of contribution, and what matters is not just how many tweets you have sent, but the value you bring to the entire project, including post engagement, sentiment, viral spread, interaction with dApps, token holding, NFT minting, or completing on-chain tasks, etc.

Mirra：Mirra is a decentralized AI model trained on community-curated data, able to learn from the real-time contributions of Web3 users. Specifically, creators posting high-quality content on X are equivalent to submitting AI validation data; Scouts identify valuable content on X and mark @MirraTerminal in replies to submit insights, determining which content the AI learns from, and helping shape intelligent AI.

Reputation-based InfoFi

Ethos is an on-chain reputation protocol, entirely based on open protocols and on-chain records, combined with Social Proof of Stake (Social PoS), which generates a credibility score through a decentralized mechanism, ensuring the reliability, decentralization, and resistance to Sybil attacks of its reputation system. Currently, Ethos operates under a strict invitation system. The core function of Ethos is to generate a credibility score, a quantified numerical indicator of a user's on-chain trust level. The score is based on the following on-chain activities and social interactions: a review mechanism (with cumulative benefits) and a guarantee mechanism (staking Ethereum to endorse other users).

Ethos also launched a reputation market, allowing users to speculate on the reputations of individuals, companies, DAOs, and even AI entities by buying and selling 'trust tickets' and 'distrust tickets', that is, longing or shorting reputation.

GiveRep: Mainly built on Sui, it aims to quantitatively convert users' social influence and community participation on the X platform into on-chain reputation through activities, and incentivize users to participate. Below the creator's post, mention GiveRep official Twitter in the comments, both the commenter and the creator will receive one reputation point each. To limit abuse, GiveRep restricts users' mention behavior to 3 times per day (including 3 times), while creators can receive unlimited points per day. Comments from Sui ecosystem projects and ambassadors will receive more points.

Attention Market / Prediction

Noise: It is a trend discovery and trading platform based on MegaETH, and currently requires an invitation code to experience. Users can focus on longing or shorting projects.

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

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

Trends: Tokenizing X posts can become a trend on the joint curve, called "Trend it". Creators are eligible to receive 20% of the joint curve transaction fees for each of your trends.

Token access control content: filter noise

Backroom: Creators can launch tokenized spaces that offer curated content such as market insights, Alpha, and analysis, without the need for management or social pressure; users can unlock low-noise, high-value information by purchasing on-chain Keys tied to each creator's space. Keys are not just for access - they are tradable assets with a demand-driven dynamic pricing curve. Meanwhile, AI processes chat data and signals into actionable insights.

Xeet: A new protocol on the Abstract network, which is not yet fully launched, but has already launched a referral program that rewards KOLs for inviting them. Xeet founder @Pons_ETH mocked the evolution of InfoFi into NoiseFi and said, "It's time to lower the noise and boost the signal." At this time, Xeet has disclosed no further information about the integration of Xeet with the use of Ethos scores.

Data Insights InfoFi

Arkham Intel Exchange: Arkham is an on-chain data querying tool, intelligence trading platform, and exchange. Arkham Intel Exchange is a decentralized intelligence trading platform where "On-chain Detectives" can earn rewards.

InfoFi dilemma

Prediction Market

• Regulation and Compliance: PredictIt markets may be seen as similar to binary options and gambling markets, facing regulatory pressure. For example, Polymarket was deemed to be operating illegally by the CFTC in the United States for not being registered as a designated contract market (DCM) or swap execution facility (SEF), fined $1.4 million in 2022, and required to block U.S. users. Investigations by the U.S. Department of Justice and FBI in 2024 further highlight its regulatory challenges.
• Insider Trading and Fairness: Predicting that the market may be affected by insider information. Large funds may distort prices in the short term. Designing fair rules and mechanisms is one of the key challenges of the InfoFi prediction market.
• Liquidity and Participation: The effectiveness of prediction markets depends on a sufficient number of participants and liquidity. Prediction markets often face a 'long-tail liquidity shortage' in niche topics, where insufficient participants lead to unreliable market information. The introduction of AI agents may partially address this issue, but further optimization is still needed.
• Oracle Design: Polymarket has encountered a situation of oracle manipulation attack, resulting in heavy losses for users who bet on the correct outcome. In February 2025, UMA, Polymarket, and EigenLayer stated that they are collaborating to research the construction of oracle for prediction markets. Some research directions include developing an oracle that can support multiple tokens to resolve disputes, while other features under study include dynamic binding, AI agent integration, and enhanced security against bribery attacks.

Mouth rolling

• The exacerbation of information noise, the proliferation of AI content advertising has obscured the true signals. Users find it difficult to filter out value from massive content, community trust decreases, and the marketing effectiveness of project parties is discounted. According to KOL CryptoBrave (@cryptobraveHQ), several project owners have complained that they spent 150,000 USDT on Kaito for services, allocating 0.5%-1% of tokens to KOLs for promotion, but most of them are AI content advertising participants. Project parties need to pay extra to attract top KOLs and ICTs to participate, and then Kaito will contact top KOLs to join.

• Most mouth-washing projects lack public explanations on how algorithms evaluate content quality, interactivity, and depth, leading to user doubts about the fairness of point distribution. If the algorithm favors specific accounts (such as big Vs or matrix accounts), it may result in the loss of high-quality creators. Recently, Kaito has made some new upgrades to the algorithm based on community feedback, with a focus on prioritizing quality over quantity, posts without project insights and comments will not receive attention, further combating interactive manipulation and group brushing behaviors, etc.

• The Matthew Effect of Profit Distribution: In most cases, projects and KOLs win-win, but tail content creators and interactive retail investors still face the dilemma of low income and fierce competition. Kaito founder Yu Hu once said on June 8th that 'Out of about 1 million registered users on Kaito, less than 30,000 users have received yaps, which is less than 3%. The next growth phase of the network is to maximize conversion rates.' In addition, poor airdrop management can lead to community dissatisfaction. Magic Newton is a relatively successful case of mouth-watering on Kaito AI. The Kaito ecosystem recommends one-third of all Newton verification agents, and mouth-watering users earn a lot, but also face criticism of being unfriendly to retail investors. In comparison, Humanity has been directly accused by the community of 'betraying users' and 'ultimate anti-laundering,' causing a trust crisis due to this distribution imbalance.

• In the early stages of the mouth-rolling activity, it attracted users to participate, but attention plummeted sharply after the rewards were distributed, lacking sustainability. The token market value of LOUD reached nearly 30 million U.S. dollars on the day of its launch, but now it is less than 600,000 U.S. dollars.

• Attention is not equal to market value proportion.

Reputation

• Reputable InfoFi projects such as Ethos adopt an invitation system to control user quality and reduce witch attacks. However, this mechanism raises the entry barrier, restricts new user access, and makes it difficult to form a broad network effect.
• Malicious operation risk.
• The cross-platform mutual recognition issue of reputation scores, the difficulty of different protocol rating systems to communicate with each other, forming information silos.

InfoFi Trends

Market Prediction

• The Combination of AI and Prediction Markets: AI can significantly enhance the efficiency of prediction markets. For example, by analyzing massive amounts of data, AI can provide more accurate predictions in complex scenarios; it can also explore AI agents to solve long-tail problems.
• The combination of social media and prediction markets: Prediction markets may become the core infrastructure of the future information economy. On June 6th, X officially announced a partnership with Polymarket, making it the official prediction market partner of X. Shayne Coplan, founder and CEO of Polymarket, said: 'Combining Polymarket's accurate, fair, and real-time prediction market probabilities with Grok's analysis and X's real-time insights will provide contextual, data-driven insights to millions of Polymarket users worldwide instantly.'
• Decentralized Governance: Prediction markets can be applied to the governance of DAOs, companies, and even societies, known as 'Futarchy.' Vitalik stated in 2014 that Futarchy is a governance model proposed by economist Robin Hanson, with the core idea of 'vote values, bet beliefs.' The operation is as follows: the community votes to determine a metric of success (such as GDP, company stock price, etc.); for specific policy proposals, two prediction markets are created (for and against). Participants trade these two tokens, with prices reflecting the market's expectations of whether the policy can optimize the target; the policy with the higher average price is ultimately chosen, and token profits are settled based on actual results. Futarchy's advantage lies in relying on data rather than political propaganda, personal charm, or promotion.
• Content and news tools for everyone.

Mouth + Reputation Type InfoFi

• Introducing social graph and semantic understanding technologies to enhance AI's accuracy in evaluating content value, ultimately moving towards high-quality content.
• Incentivize high-quality long-tail creators.
• Add reduction or penalty mechanisms.
• The release of the Web3 dedicated InfoFi LLM.
• Multi-dimensional assessment of contributions.
• InfoFi, a reputation-based project, combines with DeFi, where reputation scores serve as the credit basis for lending and collateral.
• The tokenization of abstract assets such as attention, reputation, and trends will give rise to more derivative types.
• Not only based on the X social platform.
• The integration with more social platforms and news media drives the creation of an attention, Alpha discovery tool for everyone.

Data Insights InfoFi

The combination of data analysis charts with creator insights, and the addition of incentive mechanisms related to creation, distribution, etc.

• The combination of data analysis charts and AI analysis.

Summary

The core contradiction of the digital age is the disconnection between attention creators and value holders. This disconnection is the driving force behind the Web3 InfoFi revolution.

The core contradiction of InfoFi lies in the balance between information value and incentive participation. If this balance cannot be achieved, it may repeat the mistakes of SocialFi's 'pump and dump' cycle. The key to InfoFi is to establish a 'trinity' balance mechanism, including information mining, user participation, and value return, thereby driving the formation of a better knowledge sharing and collective decision-making infrastructure. This not only requires attention quantification at the technical level but also ensures that ordinary participants can obtain reasonable returns from information dissemination in mechanism design, avoiding significant skewness in value distribution.

More importantly, the revolution of InfoFi requires a joint promotion from top to bottom and from bottom to top to truly achieve fairness and efficiency in the attention economy. Otherwise, the Matthew effect of the profit pyramid will turn InfoFi into a gold rush game for a few, running counter to the original intention of "universal attention value".

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