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A Blockchain-based Semantic Exchange Framework for Web 3.0 toward Participatory Economy

Yijing Lin, Zhipeng Gao, Yaofeng Tu, Hongyang Du, Dusit Niyato, Jiawen Kang, Hui Yang

arXiv:2211.16662v1cs.NI

TL;DR

Existing Web 3.0 solutions emphasize blockchain while leaving semantic-information trading, privacy, and fair exchange insufficiently addressed. The paper proposes an NFT-, Stackelberg game-, and zero-knowledge-proof-based semantic exchange framework, using urban planning to illustrate its mechanisms and simulations to illustrate efficiency.

  • Problem

    Current Web 3.0 solutions focus on blockchain while semantic-information pricing, fair trading, and privacy-preserving exchange remain difficult.

    Source: §I · p. 2

  • Method

    The framework tokenizes semantic information into NFTs, uses a Stackelberg game for trading and pricing strategies, and applies zero-knowledge proofs for authentic sharing before payment.

    Source: §I · p. 2

  • Results

    An urban-planning case study and simulation results illustrate the proposed framework and mechanisms.

    Source: §I · p. 2, §IV · p. 6, §VI · p. 7

  • Takeaways & Limitations

    The framework combines semantic extraction and communication with blockchain to support fair, privacy-preserving semantic exchange toward participatory economy.

    Source: §I · p. 2, C. Fair Zero-Knowledge Proof-based… · p. 5, §VI · p. 7

Abstract

from arXiv · show

Web 3.0 is the next-generation Internet that enables participants to read, write, and own contents in a decentralized manner. It is mainly driven by blockchain, semantic communication, edge computing, and artificial intelligence, which can construct value networks to achieve participatory economics based on participatory decision making. Web 3.0 can capture the characteristics of blockchain, semantic extraction, and communication to achieve decentralized semantic sharing and transfer information precisely. However, current Web 3.0 solutions focus on the blockchain while overlooking other new technologies' roles in Web 3.0. To further unleash the advantages of semantic extraction and communication in Web 3.0, in this paper, we propose a blockchain-based semantic exchange framework to realize fair and efficient interactions. In this framework, we first attempt to tokenize semantic information into Non-Fungible Token (NFT) for semantic exchange. Then we utilize a Stackelberg game to maximize buying and pricing strategies for semantic trading. We also leverage Zero-Knowledge Proof to share authentic semantic information without publishing it before receiving payments, which can achieve a fair and privacy-preserving trading compared with current NFT marketplaces. A case study about urban planning is given to show clearly the proposed mechanisms. Finally, several challenges and opportunities are identified.

I. INTRODUCTION

Web 3.0 combines blockchain, semantic communication, edge computing, and artificial intelligence to support decentralized participatory value networks, but existing solutions leave semantic trading and privacy unresolved. The paper proposes an NFT-, Stackelberg game-, and zero-knowledge-proof-based framework, illustrated through urban planning.

Research gap

  • Existing Web 3.0 approaches emphasize blockchain while giving limited attention to integrating semantic extraction, communication, and other technologies for participatory economies.Prior work includes blockchain–federated-learning and blockchain–semantic frameworks, but the paper identifies unresolved questions about circulating value and attracting participants.Source: §I · p. 1

Motivation

  • Semantic information is difficult to price and trade fairly because producers and consumers must balance revenue and utility, while public blockchains expose pending information to unpaid copying.These concerns motivate mechanisms addressing both economic incentives and privacy during semantic exchange.Source: §I · p. 2

Contributions

  • The proposed framework tokenizes semantic information into NFTs and uses a Stackelberg game to design optimal pricing strategies for semantic trading.The framework targets semantic circulation and coordinated buying and pricing strategies.Source: §I · p. 2
  • Zero-knowledge proofs transform and share semantic information without publishing authentic content before payment, supporting fair and privacy-preserving transactions.The mechanism is intended to prevent premature disclosure while enabling authentic semantic sharing between producers and consumers.Source: §I · p. 2

Application

  • An urban-planning case study demonstrates how the proposed mechanisms apply to semantic exchange and participatory decision-making.The case study is used to display how the contributions work.Source: §I · p. 2

A. An Accelerating Growth of The Internet

The Internet has progressed from read-only Web 1.0 and platform-centered read-write Web 2.0 to decentralized Web 3.0, where users can read, write, and own content. Web 3.0 combines blockchain, edge computing, artificial intelligence, and semantic communication to support efficient, decentralized value networks.

A. An Accelerating Growth of The Internet

1) What Is The Difference Between Web 1.0, Web 2.0, And Web 3.0:

  • Web 3.0 is a read-write-own web in which users control data and privacy on decentralized value networks, unlike the centralized models of Web 1.0 and Web 2.0.Web 1.0 is read-only, whereas Web 2.0 lets users read and write through platforms controlled by technology companies.Source: 1) What Is The Difference Between Web… · p. 2

2) What Is The Connection Between Web 3.0, Blockchain, Edge Computing, And Semantic Communication:

  • Blockchain supports open and trustless data sharing, edge computing provides nearby computation and storage, and artificial intelligence uses resulting data to improve services.These technologies are presented as complementary building blocks rather than interchangeable definitions of Web 3.0.Source: 2) What Is The Connection Between Web… · p. 3
  • Semantic communication conveys desired meanings rather than transmitting information only accurately, reducing information overload and energy consumption.Its role is linked to edge computing and artificial intelligence in providing efficient Web 3.0 services.Source: 2) What Is The Connection Between Web… · p. 3

3) What Are Applications of Blockchain And Semantic Communication-enabled Web 3.0:

Blockchain and semantic communication-enabled Web 3.0 targets transparent data use, decentralized exchange, and value networks across applications such as healthcare, automotive systems, and urban planning. The paper identifies integration, incentive, and fairness gaps and proposes a three-part semantic exchange framework.

3) What Are Applications of Blockchain And Semantic Communication-enabled Web 3.0:

  • Blockchain and semantic communication-enabled Web 3.0 can support healthcare, automotive, and urban-planning applications through transparent data use and decentralized exchange.These applications are presented as examples of participatory-economy use cases.Source: 3) What Are Applications of Blockchain… · p. 3

B. Research

  • Prior work largely studies blockchain or semantic-enabled Web 3.0 separately, leaving limited integration among Web 3.0, blockchain, semantic extraction, and communication.Related examples include DeSci, a unified blockchain-semantic framework, and HyperService.Source: B. Research · p. 3
  • The identified challenges are releasing semantic value, maximizing producer revenue and consumer utility, and enabling fair semantic-information trading.These challenges concern both economic incentives and transaction design in participatory economies.Source: B. Research · p. 3
  • The proposed response combines NFT-based semantic exchange, Stackelberg game-based semantic trading, and zero-knowledge-proof-based semantic sharing.Together, these mechanisms are intended to form a participatory economy around semantic information.Source: B. Research · p. 3

III. FAIR AND EFFICIENT MECHANISM BASED ON SEMANTIC BLOCKCHAIN

The framework combines NFT-based semantic circulation, Stackelberg game-based trading, and zero-knowledge-proof-based sharing to support fair and efficient semantic exchange.

III. FAIR AND EFFICIENT MECHANISM BASED ON SEMANTIC BLOCKCHAIN

  • The mechanism uses NFTs for semantic circulation, Stackelberg games for buying and pricing strategies, and zero-knowledge proofs for authentic semantic sharing.The paper presents these components as the core mechanisms of its semantic exchange framework.Source: §III · p. 3

A. NFT-based Semantic Exchange Scheme

The NFT-based scheme tokenizes semantic information as on-chain ownership credentials while using off-chain storage and blockchain-linked metadata for circulation. Its workflow supports minting, transfer, tracking, and authorized marketplace operations.

A. NFT-based Semantic Exchange Scheme

B. Efficient Stackelberg Game-based Semantic Trading Mechanism

The trading mechanism models producers’ revenue and consumers’ utility in a Stackelberg game to determine efficient buying and pricing strategies. Consumers choose required quantities first, after which producers optimize revenue given those choices.

B. Efficient Stackelberg Game-based Semantic Trading Mechanism

C. Fair Zero-Knowledge Proof-based Semantic Sharing Mechanism

The privacy-preserving sharing mechanism uses zero-knowledge proofs and transformed semantic information to balance authentic verification with protection against premature disclosure. It combines proof generation, NFT trading, and post-payment verification.

C. Fair Zero-Knowledge Proof-based Semantic Sharing Mechanism

  • Zero-knowledge proofs address the privacy and fairness problem of sharing valuable semantic information through a public blockchain.Producers avoid releasing semantic information before payment, while consumers can verify authenticity without paying for unverifiable content.Source: C. Fair Zero-Knowledge Proof-based… · p. 5
  • In Stage I, producers generate proofs for transformed semantic information using a security parameter, transform circuit, common reference string, and semantic inputs.Source: C. Fair Zero-Knowledge Proof-based… · p. 5
  • In Stage II, producers bind metadata and proofs of transformed semantic information into NFTs for trading.Source: C. Fair Zero-Knowledge Proof-based… · p. 5
  • In Stage III, consumers pay for the NFT and then verify transformed-information authenticity without revealing the underlying semantic information.Source: C. Fair Zero-Knowledge Proof-based… · p. 5

IV. CASE STUDY FOR URBAN PLANNING IN WEB 3.0

The urban-planning case study applies semantic extraction, blockchain, NFT exchange, Stackelberg trading, and zero-knowledge sharing to circulate useful spatial information fairly. The simulation compares communication overhead and examines how trading parameters affect producer revenue.

IV. CASE STUDY FOR URBAN PLANNING IN WEB 3.0

  • Extracted contours replace original urban-planning images to convey key objects and appearances while reducing information overload.Designers can use received contours to construct panoramas for urban planning.Source: §IV · p. 5
  • Urban-planning information is easy to duplicate, creating a need for trading mechanisms that provide designers with benefits and profits.Source: §IV · pp. 5–6
  • The case study uses downsized semantic contours, NFTs, and Stackelberg marketplaces to enable fair and efficient exchange among urban designers.Zero-knowledge sharing avoids releasing core designs before exchange, while NFTs support circulation and trading.Source: §IV · p. 6
  • The proposed mechanism has lower communication overhead than traditional communication and the unified blockchain-semantic baseline in Fig. 4(a).The comparison uses transmitted-message sizes of 1 MB, 100 KB, and 1 KB for the three mechanisms.Source: Figure 4 · p. 5, §IV · p. 6
  • Increasing semantic-trading parameters raises cost weight in the producer revenue function and decreases income as iterations increase.Source: §IV · p. 6

V. OPEN CHALLENGES AND FUTURE DIRECTIONS

The paper identifies open challenges spanning privacy-preserving semantic verification, NFT pricing, interoperability across chains and tasks, and resource-efficient semantic exchange.

Verification of Semantic Information

  • Semantic verification must share private, authentic information without publishing it, while reputation mechanisms can help exclude malicious participants.Zero-knowledge proofs support verification through mathematical relationships, particularly in privacy- and security-sensitive scenarios.Source: §V · p. 6

Price Bubbles of NFT-mapped Semantic Information

  • NFT-based semantic assets remain vulnerable to price bubbles in current marketplaces, motivating English Dutch auctions as a possible remedy.OpenSea is cited as an example of a current market mechanism where price bubbles are difficult to avoid.Source: §V · p. 6

Semantic Interoperability

  • Semantic interoperability must cover information exchanged across multiple blockchains and common characteristics extracted across different semantic tasks.Cross-chain technologies combined with verification address the former scope, while task alignment addresses the latter.Source: §V · p. 6

Task-Oriented Layer 2 Solutions

  • Continuous semantic-information exchange after environmental perception is time- and resource-consuming, creating a role for decentralized, traceable Layer 2 off-chain interactions.Current Layer 2 solutions are presented as a practical way to improve blockchain and semantic-communication performance.Source: §V · p. 7

VI. CONCLUSION

The paper proposes a fair and efficient blockchain-based semantic exchange framework for participatory economy. It combines NFT circulation, Stackelberg-game trading strategies, and zero-knowledge proofs, illustrated through urban-planning case studies and simulations.

Conclusion

  • The framework uses NFTs for semantic-information circulation, Stackelberg games for buying and pricing strategies, and zero-knowledge proofs for authentic semantic sharing.The paper also reports an urban-planning case study and simulation results to illustrate the framework's efficiency.Source: §VI · p. 7

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