Online social platforms for digital communication necessitate an in-depth understanding of their evolving dynamics, especially after the renewal requests brought about by new paradigms, such as Web3. The dynamics within online social networks (OSNs) are influenced by numerous factors, encompassing user behavior, content generation, platform features, and technological advancements, with triadic closure standing out as a prominent and influential element. In this study, we focus on the temporal aspects of triadic closure and its role in the evolution of OSNs, especially after the advent of the Web3 paradigm. By analyzing networks with timestamped links from diverse platforms based on different architectures, including communication, Web3-based, and trade networks, we developed a comprehensive analytical pipeline to support the study of triadic closure patterns. This pipeline includes an algorithm for the census of time-ordered triads, a vector-based model for representing growing networks (growth triadic profile), the identification of triadic closure rules (TERs), and the evaluation of the speed of the formation of closed triads. Our findings reveal significant variations in the impact of triadic closure across different OSNs, marked by diverse growth triadic profiles and varying formation speeds of closed triads as well as diversity in the predictability of evolutionary patterns based on triads. This study not only enhances the comprehension of triadic closure in the temporal evolution of OSNs but also provides valuable insights to be taken into account for the design and administration of online social platforms.
In recent years, the Ethereum Name Service (ENS) has garnered significant attention within the community for enabling the use of Unicode in domain names, thereby facilitating the inclusion of a wide array of character sets such as Greek, Cyrillic, Arabic, and Chinese. While this feature enhances the versatility and global accessibility of domain names, it concurrently introduces a substantial security vulnerability due to the presence of homoglyphs-characters that are visually similar to others across Unicode and ASCII sets. These similarities can be exploited in homoglyph attacks, posing a distinct threat to domain name integrity. Despite community efforts to counteract this issue through a normalization process prior to domain resolution, our analysis uncovers significant discrepancies in how the normalization processes are applied across various applications. This inconsistency could result in the same domain name being resolved to different addresses in different applications, underscoring a critical vulnerability. We also discovered the new attack scenario in ENS which may cause legitimate domains resolved into malicious addresses even when they are verified by authorities. To systematically evaluate this inconsistency, we designed a tool for detecting application-level discrepancies in domain normalization process without requiring access to the application's source code. Our evaluation on hundreds of real-world Web3 applications identifies widespread deviations from established homoglyph mitigation practices, with more than 60% digital wallets and 80% dApps (decentralized applications) not able to produce consistent ENS resolving results, potentially impacting millions of users. This analysis underscores the urgent need for a standardized implementation of normalization processes to safeguard the integrity and security of ENS domains.
In recent years, a large number of on-chain attacks have emerged in the blockchain empowered Web3 ecosystem. In the year of 2023 alone, on-chain attacks have caused losses of over 585 million. Attackers use blockchain transactions to carry out on-chain attacks, for example, exploiting vulnerabilities or business logic flaws in Web3 applications. A wealth of efforts have been devoted to detecting on-chain attack transactions through expert patterns and machine learning techniques. However, in this ever-evolving ecosystem, the performance of current methods is limited in detecting new on-chain attacks, due to the obsoleting of attack recognition patterns or the reliance on on-chain attack samples. In this paper, we propose a universal approach for detecting on-chain attacks even when there are few or even no new on-chain attack samples. Specifically, an in-depth analysis of the transaction characteristics is conducted, and we propose a new insight to train a generic attack transaction detecting model, i.e., transaction reconstruction. Particularly, to overcome the over-fitting in the transaction reconstruction task, we use the web-scale function comments related to transactions as supervision information, rather than expert-confirmed labels. Experimental results demonstrate that the proposed approach surpasses the supervised state-of-the-art by 13% in AUC, with just 30 known on-chain attack samples. Moreover, without any known attack samples, our method can still detect new on-chain attacks in the wild (with a precision of 61.83%). Among attacks detected in the wild, we confirm 1,692 address poisoning attacks, a new type of on-chain attack targeting token holders. Our code is available at: https://github.com/wuzhy1ng/attack_trans_detection_www25.
Isaac Zhang, Kshitij Kulkarni, Tan Li, Daniel Wong · 9 authors
Blockchain technology promises a decentralized, trustless, and interoperable infrastructure. However, widespread adoption remains hindered by issues such as limited scalability, high transaction costs, and the complexity of maintaining coherent verification logic across different blockchain layers. This paper introduces Verifiable Applications (vApps), a novel development framework designed to streamline the creation and deployment of verifiable blockchain computing applications. vApps offer a unified Rust-based Domain-Specific Language (DSL) within a comprehensive SDK, featuring modular abstractions for verification, proof generation, and inter-chain connectivity. This eases the developer's burden in securing diverse software components, allowing them to focus on application logic. The DSL also ensures that applications can automatically take advantage of specialized precompiles and hardware acceleration to achieve consistently high performance with minimal developer effort, as demonstrated by benchmark results for zero-knowledge virtual machines (zkVMs). Experiments show that native Rust execution eliminates interpretation overhead, delivering up to an 197x cycle count improvement compared to EVM-based approaches. Precompiled circuits can accelerate the proof by more than 95%, while GPU acceleration increases throughput by up to 30x and recursion compresses the proof size by up to 230x, enabling succinct and efficient verification. The framework also supports seamless integration with the Web2 and Web3 systems, enabling developers to focus solely on their application logic. Through modular architecture, robust security guarantees, and composability, vApps pave the way toward a trust-minimized and verifiable Internet-scale application environment.
The Web3 ecosystem, underpinned by cryptographic primitives and decentralized consensus, represents a high-stakes environment where software vulnerabilities and incentive misalignments translate directly into financial loss. As Large Language Models (LLMs) are increasingly integrated into this domain for tasks ranging from smart contract auditing to decentralized finance analytics, ensuring their reliability is paramount. However, general-purpose benchmarks fail to capture the specialized reasoning required for these adversarial and protocol-driven settings. To bridge this gap, we introduce DMind Benchmark, a comprehensive evaluation suite designed to rigorously assess LLM proficiency across the Web3 stack. DMind Benchmark encompasses nine distinct subdomains (spanning infrastructure, smart contracts, token economics, etc.) and combines objective knowledge retrieval with complex open-ended reasoning tasks that emulate real-world operational challenges. We conduct an extensive evaluation of 31 leading proprietary and open-weights models, employing a contamination-aware pipeline and verifying the statistical robustness of our scoring protocol through rigorous cross-judge consistency checks. Our analysis reveals a critical dichotomy: while models demonstrate competence in foundational infrastructure concepts, they exhibit significant vulnerabilities in high-reasoning tasks such as security auditing. Furthermore, we provide a Pareto analysis to guide cost-effective deployment and demonstrate through adversarial experiments that high performance on DMind Benchmark necessitates genuine reasoning rather than superficial memorization. Since its open-source release in April 2025, DMind Benchmark achieved the #1 trending position on Hugging Face for nearly a week and accumulated over 13k downloads by June 2026, establishing itself as a standard for advancing secure and trustworthy AI in Web3.
Kai Ma, Ningyu He, Jintao Huang, B. X. Zhang · 6 authors
Cybersquatting refers to the practice where attackers register a domain name similar to a legitimate one to confuse users for illegal gains. With the growth of the Non-Fungible Token (NFT) ecosystem, there are indications that cybersquatting tactics have evolved from targeting domain names to NFTs. This paper presents the first in-depth measurement study of NFT cybersquatting. By analyzing over 220K NFT collections with over 150M NFT tokens, we have identified 8,019 cybersquatting NFT collections targeting 654 popular NFT projects. Through systematic analysis, we discover and characterize seven distinct squatting tactics employed by scammers. We further conduct a comprehensive measurement study of these cybersquatting NFT collections, examining their metadata, associated digital asset content, and social media status. Our analysis reveals that these NFT cybersquatting activities have resulted in a significant financial impact, with over 670K victims affected by these scams, leading to a total financial exploitation of $59.26 million. Our findings demonstrate the urgency to identify and prevent NFT squatting abuses.
Damodar Bihani, Bright Chibunna Ubamadu, Andrew Ifesinachi Daraojimba
The evolution of Web3 has ushered in a paradigm shift from centralized control to decentralized, user-centric ecosystems powered by blockchain technology. At the core of these ecosystems lies tokenomics—the strategic design and management of token economies—which plays a crucial role in ensuring long-term sustainability, scalability, and user engagement. This paper presents a strategic framework for understanding and optimizing tokenomics within Web3 ecosystems, integrating insights from game theory, behavioral economics, and blockchain governance. It identifies key components of effective tokenomic models, including token utility, supply mechanisms, distribution strategies, and incentive alignment. The proposed framework emphasizes the importance of balancing inflationary and deflationary forces, designing value accrual mechanisms that benefit both users and network developers, and embedding governance protocols that enhance transparency and resilience. Additionally, this study explores the interplay between token utility and network effects, underscoring how strategic token design can accelerate ecosystem growth while maintaining decentralization. By analyzing successful Web3 projects such as Ethereum, Polkadot, and Cosmos, the paper extracts best practices and highlights potential pitfalls that hinder ecosystem scalability and trust. Furthermore, it evaluates regulatory implications, sustainability challenges, and market volatility, proposing adaptive policy mechanisms to future-proof token economies. The framework provides a roadmap for developers, investors, and policymakers aiming to build or assess blockchain ecosystems that are not only technologically sound but also economically viable. In doing so, this research bridges the gap between technical blockchain design and economic sustainability, offering actionable insights for fostering inclusive, community-driven, and robust Web3 infrastructures. As blockchain adoption accelerates globally, strategic tokenomics will be pivotal in shaping the next generation of digital economies, ensuring equitable value creation and distribution in decentralized environments.
Extended reality holds the potential to alter human experiences. This project explores user perceptions of peak experience (PE), a state of self-actualization and fulfillment, within augmented spaces and the potential role it can play for designers and developers to effectively engage immersive World Wide Web (Web3) communities. Semi-structured interviews, including an interactive experience stimulus, with key stakeholders in the Web3 space (staff from global immersive technology entities, brand collaborators, and community members, n = 15) were conducted. The findings reveal rich opportunities for users to experience surprise, delight, and a sense of connection and belonging in these spaces. They further suggest the potential to reshape and extend current user experiences by moving the focus of design toward crafting PEs. This holds great value for users to achieve a fuller sense of self-actualization and for content creators to connect to their communities in more meaningful ways.
The prevalence of counterfeit medicines poses a significant threat to public health and safety, largely due to the opaque nature of traditional medicine supply chains. This research introduces a blockchain-based solution designed to bring transparency, traceability, and enhanced security to the medicine distribution process. The proposed system records every transaction in the supply chain, thereby preventing tampering and ensuring the authenticity of pharmaceutical products. Smart contracts are utilized to automate the verification and transfer of products between stakeholders such as manufacturers, distributors, and retailers. A decentralized application (DApp) was developed using React to facilitate user interaction, while the backend was implemented using the Truffle framework and connected to a local Ethereum blockchain via Ganache and Web3.js. The system supports real-time tracking of medicines and reduces dependency on intermediaries, which not only improves operational efficiency but also enhances the overall integrity of the supply chain. This blockchain-based approach represents a significant advancement over conventional methods by offering a transparent, tamper-resistant, and verifiable solution for medicine supply chain management. Keywords: Blockchain, Smart Contracts, Drug Counterfeiting, Supply Chain, Product Traceability, Security.
This paper investigates the impact of cross-chain deployment on the market performance of decentralized applications (Dapps) within the evolving multichain Web3 ecosystem. While cross-chain Dapps benefit from broader user reach, improved scalability, and enhanced resilience, they also face significant challenges, including technical complexities, security risks, and fragmented liquidity. This paper analyses how Dapps' transaction distribution across multiple blockchains influences their market performance. Preliminary findings reveal that Dapps operating on multiple chains tend to underperform in terms of market capitalization, token price, and transaction volume compared to those concentrated on a single or few chains. These results highlight critical concerns about the effectiveness of cross-chain strategies.
This paper introduces Web3DB, a decentralized relational database management system (RDBMS) designed to align with the principles of Web 3.0, addressing critical shortcomings of traditional centralized DBMS, such as data privacy, security vulnerabilities, and single points of failure. Several similar systems have been proposed, but they are not compatible with the legacy systems based on RDBMS. Motivated by the necessity for enhanced data sovereignty and the decentralization of data control, Web3DB leverages blockchain technology for fine-grained access control and utilizes decentralized data storage. This system leverages a novel, modular architecture that contributes to enhanced flexibility, scalability, and user-centric functionality. Central to the Web3DB innovation is its decentralized query execution, which uses cryptographic sortition and blockchain verification to ensure secure and fair query processing across network nodes. The motivation for integrating relational databases within decentralized DBMS primarily stems from the need to combine the robustness and ease of use of relational database structures with the benefits of decentralization. This paper outlines the architecture of Web3DB, its practical implementation, and the system's ability to support SQL-like operations on relational data, manage multi-tenancy, and facilitate open data sharing, setting new standards for decentralized databases in the Web 3.0 era.
Cheick Tidiane Bâ, Benjamin A. Steer, Matteo Zignani, Richard G. Clegg
Blockchain technology and cryptocurrencies have garnered considerable attention over the past 15 years. The term Web3 (sometimes Web 3.0) has been coined to define a possible direction for the web based on the use of decentralisation via blockchain. Cryptocurrencies are characterised by high market volatility and susceptibility to substantial crashes, issues that require temporal analysis methodologies able to tackle the high temporal resolution, heterogeneity, and scale of blockchain data. While existing research attempts to analyse crash events, fundamental questions persist regarding the optimal timescale for analysis, differentiation between long-term and short-term trends, and the identification and characterisation of shock events within these decentralised systems. This article addresses these issues by examining cryptocurrencies traded on the Ethereum blockchain, with a spotlight on the crash of the stablecoin TerraUSD (UST) and the currency LUNA designed to stabilise it. Utilising complex network analysis and a multi-layer temporal graph allows the study of the correlations between the layers representing the currencies and system evolution across diverse timescales. The investigation sheds light on the strong interconnections among stablecoins pre-crash and the significant post-crash transformations. We identify anomalous signals before, during, and after the collapse, emphasising their impact on graph structure metrics and user movement across layers. This article is novel in its use of temporal, cross-chain graph analysis to explore a cryptocurrency collapse. It emphasises the importance of temporal analysis for studies on web-derived data. In addition, the methodology shows how graph-based analysis can enhance traditional econometric results. Overall, this research carries implications beyond its field, for example, for regulatory agencies aiming to safeguard users could use multi-layer temporal graphs as part of their suite of analysis tools.
Advances in digital technology - particularly Web3’s pseudonymity and decentralized naming systems, combined with information flows’ anonymity, accessibility, and cross-border nature - enable terrorist organizations to recruit members and perpetrate discrete socially dangerous acts. Conventional reactive counterterrorism measures prove inadequate against rapid illicit content dissemination that leaves detectable digital traces. This study explores artificial intelligence’s (AI) counter-criminal potential on machine learning and predictive analytics for proactively identifying and preventing terrorist activity through behavioral indicators and digital footprints that facilitate a strategic shift to proactive security paradigms. The research develops a multimodal analytical framework integrating natural language processing, computer vision, audio analysis, and social network analysis, detailing the complete machine learning pipeline from data preprocessing to model deployment. It examines the “RED-Alert” system as practical implementation and proposes a novel “Threshold Adaptive Intervention” (PORA) module utilizing graph neural networks and time-series analysis for digital risk assessment. Machine learning excels at threat detection and digital evidence generating, necessitating reevaluation of internet service providers’ (ISP) liability - particularly collective digital inaction. A differentiated liability framework accounts for providers’ technical influence while treating AI-derived risk indicators as ancillary tools for establishing individual culpability. Machine learning and predictive analytics enable a strategic shift to proactive counterterrorism.
Open access
Terrorism, Counterterrorism, and Political Violence
Purpose Non-fungible tokens (NFTs) are reshaping art markets and gaining strong stakeholder interest. While research has examined their applications in art ecosystems, their role in advancing Web3D markets remains unclear. Design/methodology/approach A systematic literature review was conducted to investigate the impact of NFTs on the Web3D market and its impact on stakeholders, analysing 89 systematically selected articles. Findings The results of the study show that NFTs in the Web3D context can enhance privacy and trust through blockchain technology and protect intellectual property and ownership rights while influencing market dynamics, behaviour and investment strategies. Originality/value As the Web3D ecosystem grows, ongoing research and collaboration are critical to developing strategies that ensure sustainability, transparency and innovation in digital arts. This study is the first step in exploring these dynamics. Highlights
This paper examines the hesitancy of Australian musicians towards embracing the music non-fungible token (NFT) as a commodity. Drawing on the concepts of cultural autonomy and the digital disruptive sublime, the study argues that the overtly economic nature of NFTs challenges the ideology of creative independence in the hegemonic ‘indie’ music scene. Through interviews with nine Australian musicians who participated in our project, the research finds a cautious curiosity towards the technology, with technical barriers and a perceived cultural disconnect between the NFT ‘community’ and traditional music scenes contributing to hesitation. The paper concludes that attempts to engineer disruption in the music industry through web3/blockchain technology have thus far failed to attract sustained interest from musicians, as the cultural norms and practices associated with NFTs do not align with the values of the existing indie music ecosystem. The findings highlight the difficulties in planning and engineering cultural change within the music industry.
This paper presents a project aims to develop a decentralized, blockchain-powered online multiplayer card game designed to enhance transparency, security, and fairness in gameplay. By leveraging smart contracts and distributed ledger technology, the game ensures truthful interactions between players, eliminating intermediaries and providing verifiable outcomes. Each in-game action such as card transactions, player interactions, and match results is recorded on the blockchain, ensuring immutability and transparency. Players retain full ownership of their in-game assets, represented as non-fungible tokens (NFTs), allowing them to trade, sell, or utilize their assets across various platforms. The project integrates Web3 technologies to deliver a seamless user experience while blending traditional card game mechanics with decentralized gaming principles, ultimately creating a secure, engaging, and player-driven multiplayer environment.
Sang-Hyeon Park, Jeonghyuk Lee, Seunghwa Lee, Jung Hyun Chun · 8 authors
Merging Internet (web2) identities with blockchain (web3) identities is increasingly important for enhancing user experience and ensuring regulatory compliance. However, conventional solutions that map web2 identities to web3 accounts often lead to privacy concerns and fragmented identifiers across networks. To address these challenges, we propose a new identity scheme named Address Abstraction (AA), which redefines blockchain address and signing systems while preserving key properties: uniqueness, immutability, and privacy-preservation. This approach eliminates the limitations of chain-specific identity systems, enabling users to interact with multiple blockchains using their web2 certificates and unified identifiers. This chain-agnostic identifier also promotes cross-chain compatibility. We further present Zero-Knowledge Address Abstraction (zkAA), an implementation of AA that uses zero-knowledge proofs to uphold AA's core properties. Additionally, a proof aggregation technique combines multiple proofs into one, achieving approximately 5.5 times gas cost savings during verification in real-world scenarios. As of August 2024, zkAA with proof aggregation incurs an additional cost of only $0.66 per transaction on Ethereum.
Mother of all Bitcoins and cryptocurrencies but why haven’t we seen the latent potency this technology could bring to the world in this era. Blockchain is THE revolutionary change which is going to predominantly realign every facet of business and technology. Beginning from storage of data till public voting, a blockchain can drastically transform day to day activities even to a laymen. It is predicted at least 10% of global GDP (Gross Domestic Product) will be stored on a blockchain. Technically briefing, this is not just turning to be an aid to organizations and society but it is employing into a comprehensive replacement of the whole extensive process. Industry 4.0, Web3.0, Decentralized Autonomous Organizations, Smart Contracts are latest modernizations going to dictate the world very soon.
S Sudhip, Pratyush Sthapit, S. Maheshwari, Samarjit Sahu · 5 authors
Abstract: In today's fast-paced world, tracking personnel has become a necessity for various organizations, especially in industries such as Police Department, and security. The use of Near Field Communication (NFC) devices has emerged as a promising technology for tracking personnel. This paper presents a study on the feasibility and benefits of tracking personnel using NFC devices. Our study is based on NFC (Near Field Communication) which is A wireless communication technology that allows two devices to Exchange data when they are brought into proximity. NFC when used in reader/writer mode NFC device can read From NFC transponders or NFC writer. NFC when used in peerTo-peer mode NFC can be used to exchange information Between two NFC enabled devices and in card emulation mode NFC device can be used with Contactless Card for various Purposes like paying money or exchanging information Security of NFC device can be ensured by various means of Encryption and now we have new web3 technology.
Abstract The convergence of artificial intelligence (AI) and blockchain technology is transforming the creative economy by enabling secure, transparent, and decentralized innovation in digital content creation, intellectual property management, and monetization. Traditional creative industries are often constrained by centralized platforms, opaque copyright enforcement, and unfair revenue distribution, which limit the autonomy and financial benefits of creators. By leveraging blockchain’s immutable ledger, smart contracts, and non-fungible tokens (NFTs), digital assets can be authenticated, tokenized, and securely traded, ensuring ownership verification and automated royalty distribution. Simultaneously, AI-driven tools such as generative adversarial networks (GANs), neural networks, and natural language processing (NLP) models facilitate content generation, curation, and adaptive recommendations, enhancing creative workflows and fostering new artistic possibilities. This research report explores the synergies between AI and blockchain in the decentralized creative economy, analyzing their impact on digital rights protection, NFT marketplaces, decentralized publishing, AI-assisted music composition, and smart licensing models. Furthermore, it examines regulatory challenges, ethical considerations, and scalability limitations that need to be addressed for mainstream adoption. By integrating AI-powered automation with blockchain’s decentralized infrastructure, this study outlines a sustainable roadmap for secure, fair, and transparent digital creativity in the Web3 era. Keywords AI-powered creativity, blockchain-based digital ownership, decentralized innovation, generative AI, smart contracts, non-fungible tokens (NFTs), digital content authentication, AI-driven content generation, decentralized autonomous organizations (DAOs), intellectual property management, AI in art and music, Web3 creativity, tokenized digital assets, secure content monetization, ethical AI in blockchain, AI-assisted copyright protection, decentralized publishing, AI-powered music composition, blockchain scalability, AI for digital rights management.
Kode Lakshmi Durga Sindhujasri, Kaduputla Manogna, Sutrayeth Hari Yuktha Nanda, Baligiri Thandava Krishna · 5 authors
Abstract: Elections play a fundamental role in any democratic system, and ensuring their integrity is of utmost importance. Traditional voting methods, such as paper ballots and Electronic Voting Machines (EVMs), suffer from various limitations, including security vulnerabilities, vote tampering, low voter turnout, delays in result processing, and a lack of transparency. Digital voting solutions offer convenience but raise concerns regarding data security and susceptibility to cyber threats. Blockchain technology presents a promising solution to these challenges by providing a decentralized, transparent, and tamperproof framework for conducting elections. As a distributed ledger system, blockchain records transactions in an immutable and verifiable manner, ensuring the integrity of votes. Key features such as decentralization, cryptographic security, transparency, and anonymity make blockchain a robust choice for secure e-voting. In this paper, we propose and implement a blockchainbased e-voting system using Ethereum smart contracts and Web3.js. Our system enforces single-use voting credentials, preventing duplicate votes, and leverages gas fees to mitigate fraudulent voting attempts. Additionally, we develop a web-based application that demonstrates the practical implementation of blockchain voting, discussing its advantages, challenges, and limitations in real-world scenarios
Open access
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
AI agents integrated with Web3 offer autonomy and openness but raise security concerns as they interact with financial protocols and immutable smart contracts. This paper investigates the vulnerabilities of AI agents within blockchain-based financial ecosystems when exposed to adversarial threats in real-world scenarios. We introduce the concept of context manipulation -- a comprehensive attack vector that exploits unprotected context surfaces, including input channels, memory modules, and external data feeds. It expands on traditional prompt injection and reveals a more stealthy and persistent threat: memory injection. Using ElizaOS, a representative decentralized AI agent framework for automated Web3 operations, we showcase that malicious injections into prompts or historical records can trigger unauthorized asset transfers and protocol violations which could be financially devastating in reality. To quantify these risks, we introduce CrAIBench, a Web3-focused benchmark covering 150+ realistic blockchain tasks. such as token transfers, trading, bridges, and cross-chain interactions, and 500+ attack test cases using context manipulation. Our evaluation results confirm that AI models are significantly more vulnerable to memory injection compared to prompt injection. Finally, we evaluate a comprehensive defense roadmap, finding that prompt-injection defenses and detectors only provide limited protection when stored context is corrupted, whereas fine-tuning-based defenses substantially reduce attack success rates while preserving performance on single-step tasks. These results underscore the urgent need for AI agents that are both secure and fiduciarily responsible in blockchain environments.
This study examines the representation and evaluation of Web3 technology in the German music media from 2016 to 2022, focusing on its prevalence, framing, and acceptance in the context of the music sector. Utilizing framing theory and the Technology Acceptance Model, a quantitative content analysis was conducted on articles from various music magazines. The findings indicate a generally positive portrayal of Web3, with significant discussion peaks in 2019, 2021, and 2022. Notably, no coverage was found in music education magazines, suggesting a gap in Web3 engagement in pedagogy. Much of the coverage was in Musikwoche, highlighting Web3’s impact on business aspects like ticketing, copyright, and licensing. The overall positive depiction, juxtaposed with limited critical evaluation, points to the need for a more nuanced discourse. The study underscores implications for balanced media coverage, informed musician engagement with Web3, and the potential for incorporating this technology in music education. It highlights the importance for the music industry of capitalizing on Web3’s positive aspects while practising critical awareness, and it calls for further research to explore the depth of Web3’s influence in music.