Andrea Michienzi, Laura Pollacci, Barbara Guidi, Francesco Maggio
Nowadays, Social Media represents an important window to address societal issues and promote social causes. However, Social Media suffer from several issues concerning fake news, misinformation, disinformation, etc. To address these issues, decentralization has been proposed to overcome current limitations. Blockchain-based Online Social Media (BOSM) offer verifiable platforms, usually enriched with reward systems that allow users to get paid according to the social value they create. Reward systems can economically empower creators and other individuals beyond high-quality content, allowing content creators to earn income. Considering the widespread use of BOSM platforms and various incentive methods, tools are needed to analyze and guide these rewarding strategies to avoid the risk of speculative mechanisms. In this paper, we propose BISON, a predictive and interpretable framework for identifying the drivers of success in blockchain-native articles. BISON can model success not as a purely financial outcome, but as a composite function of content attributes and user engagement patterns, as recorded on the blockchain. Its modular architecture allows for empirical validation across multiple datasets and makes it adaptable to other Web3 platforms. Additionally, our framework introduces Explainable AI into the blockchain content domain.
Anthony Sai Richardo, Franz Adeta, Yohan Muliono, Michelle Hamjaya · 5 authors
Web3 airdrops have become a popular way to distribute tokens and raise project awareness, but their objective is frequently abused by bot activities. For example, the 2024 Hamster Kombat project reported detecting over 2.3 million automated bot interactions during its airdrop event. To address the problem, this research compares seven supervised machine learning models for detecting bot activity in Telegram-based Web3 airdrops by analyzing patterns in API requests. A total of 2600 data entries were collected: 1300 from real bot scripts and 1300 manually gathered using Telegram's built-in network tools. Each sample contains technical features such as HTTP request methods, URLs, request headers, and public IP addresses. These were further enriched with indicators of VPN usage, proxy connections, TOR relay presence, and whether the IP address was linked to a hosting provider. The result shows Gaussian Naïve Bayes and the MLP Classifier were the top performers, with$\mathbf{9 4. 4 1 \%}$validation accuracy,$\mathbf{9 4. 0 0 \%}$test accuracy, and 84.56 % accuracy when evaluated on a separate set of new data. These models accurately captured statistical patterns in bot data and complex interactions in human data. The results emphasize the importance of machine learning in securing Web3 token distribution processes.
Quentin Botha, Laurent Bindschaedler, Christoph Siebenbrunner
Decentralized mathematics prediction markets promise new forms of collaboration and incentive alignment, but traditional requirements engineering methods fail to address the unique governance, incentive, and security challenges of such Web3 systems. This paper demonstrates how they can be addressed through a requirements-driven design of a decentralized prediction market for mathematical conjectures, and proposes concrete enhancements to existing frameworks. Our work delivers actionable guidelines for engineering secure, incentive-aligned decentralized platforms, and sets a new standard for early-stage RE in the Web3 era.
The integration of distributed digital twins (DTs) within an industrial metaverse presents a significant challenge to system stability and predictability. Continuous, asynchronous updates to individual DTs and their underlying generative AI foundation models create dynamic interdependencies that traditional, centralized requirements management systems cannot adequately govern due to inherent issues of trust, transparency, and data integrity. This paper argues for a paradigm shift, proposing a decentralized, multi-party requirements management framework built on Web3 distributed ledger technology. In this approach, requirements are transformed from static documents into immutable, traceable transactions on a shared ledger, with their validation and enforcement automated through smart contracts. The proposed system establishes a single, verifiable source of truth, enabling the use of automated guardrails and negotiated adjustments to contain the impact of changes. This ensures that the complex mesh of DTs can co-evolve in a stable, predictable, and secure manner, addressing key barriers and fostering the adoption of a collaborative industrial metaverse, as illustrated through a practical semiconductor manufacturing use case.
Itzhak Aviv, Alfred Taudesh, Davor Svetinović, Seok Won Lee
The second International Workshop on Requirement Engineering for Web3 Systems (RE4Web3), held at the 33rd IEEE RE Conference 2025 in Valencia, Spain. RE4Web3 fills in the space between traditional Requirements Engineering (RE) and particular challenges posed by Web3 technologies. Systems based on Web3 engineering principles are transforming software ecosystems with economic tools, transparent ledgers, and decentralized governance. This transition violates assumed expectations in requirements engineering, which mandates adjustments to traditional system engineering frameworks. A research agenda across quantum-safe security, autonomous agent control, socio-technical governance, token incentive design, and supply-chain transparency is advanced in seven peer-reviewed papers.
The unprecedented rise of Bitcoin has marked a significant milestone in the evolution of decentralized finance (DeFi). Despite Bitcoin's groundbreaking contributions, it faces inherent challenges due to its reliance on the Unspent Transaction Output (UTXO) model, which limits its capabilities in executing complex transactions and embedding diverse data types. To overcome these limitations, Ordinals and Inscriptions have been introduced, allowing extensive data and information embedding within Bitcoin transactions. Building upon these advancements, the recent development of the BRC-20 standard leverages these capabilities to introduce fungible tokens on the Bitcoin network. However, these innovations have yet to be fully integrated into the broader blockchain and DeFi ecosystems, and they still face challenges related to interoperability, scalability, and user perception. In this paper, we explore the intricacies of Ordinal, Inscription, and BRC protocols to address these challenges by analyzing their functionalities, operational methodologies, and potential applications. We offer a detailed examination of the challenges and future prospects, shedding light on the unexplored potential of these technologies in transforming Bitcoin transactions and expanding its role in the DeFi space. By thoroughly analyzing these new developments, we aim to bridge the gap in current academic research and offer valuable insights for developers, investors, and enthusiasts. This paper serves as a foundation for future innovations, paving the way for more robust, scalable, and user-friendly applications in the DeFi and Web3 landscape.
Tecnológico de Estudios Superiores del Oriente del Estado de México, Benito Samuel López Razo, José Israel Campero Domínguez, Víctor Hugo de la O Martínez · 7 authors
La emisión de documentos oficiales en el ámbito educativo a nivel superior se ha comprometido en los últimos años en México debido a la falsificación y robo de identidad. Esta investigación presenta un sistema distribuido basado en Blockchain y Ethereum para la emisión y validación de certificados digitales, garantizando seguridad, trazabilidad e inmutabilidad mediante contratos inteligentes escritos en Solidity. Utilizando la biblioteca web3.py y la red Ethereum. El sistema integra firmas digitales X.509, ERC-721 y códigos QR para facilitar la verificación. Los resultados preliminares muestran métricas de gas usado y consumo de recurso Ethereum de 0.00442378 en promedio por transacción. Este enfoque ofrece una solución escalable y confiable para la emisión y gestión de certificados en entornos educativos e industriales. El sistema reduce costos de verificación en un 43% en comparación de un sistema distribuido con sistemas centralizado.
This study examines how the historical development of web technologies and Korea’s digital transformation have shaped the structure of art consumption, situating the inquiry within broader socio-historical flows and institutional frameworks. The trajectory from the static information delivery of Web 1.0, to the interactive platforms of Web 2.0, to the semantic and relational information sharing of Web 3.0, and finally to the decentralization of Web3, extends beyond a mere technological evolution. In particular, the state-led informatization policies initiated in the wake of the 1997 IMF financial crisis, along with subsequent strategies such as the Digital New Deal, laid the institutional foundation for the digital transformation of the Korean art market. Within this context, the study traces the processes and changes in art consumption that emerged. Methodologically, the research adopts a qualitative, interpretive approach, drawing upon diverse secondary sources including academic studies, policy documents, news reports, and platform operation records. The findings demonstrate that web technologies have served as a primary driver of comprehensive changes in art—shaping modes of appreciation, systems of distribution, and extending further into assetization and financialization. Today, art consumption has been redefined to move beyond viewing and purchasing, encompassing decentralized experiences and transactions as assets via online platforms. This shift underscores the rise of platform-based relational consumption models and the structural incorporation of art into capital markets. The study’s significance lies in its diachronic analysis of how web technologies have impacted art consumption. Furthermore, by integrating perspectives from the histories of technology, policy, and art, it establishes a foundation for multi-layered inquiry into the transformations of art consumption and institutional frameworks.
Security protection of dynamically generated log files requires immediate prevention against alteration, reliability, and compliance of current systems. The research creates a novel framework that integrates blockchain technology with cryptographic hashing methods to establish resistant and immutable log authentication mechanisms. The system dynamically generates log files through Python while saving a cryptographic hash (SHA-256) for verification of file integrity. Security and authentication of these hashes occurs through an Ethereum blockchain smart contract named Sepolia testnet. The framework uses Remix IDE along with Web3.py through Infura to connect into the Ethereum Sepolia testnet for launching smart contracts development. Simulation results demonstrated the system effectiveness by showcasing how logs remain immutable while providing performance data including transaction processing time and gas usage and event output. The research demonstrates how blockchain technology can power real-time log verification systems and suggests foundations for future decentralized security system developments.
The article explores the evolution of marketing innovations in the retail sector through the lens of technological development and the transformation of consumer expectations. Five key stages of innovation development are identified—traditional, network based, digital, omnichannel, and innovation-technological—each characterized by specific challenges, opportunities, and influencing factors. The traditional stage was marked by a focus on product policy and individual promotions within the physical store. The network-based stage introduced the integration of IT solutions into logistics, CRM systems, and initial customer segmentation. The digital stage was distinguished by the emergence of online stores, mobile marketing, and personalized communication. The omnichannel stage involved the full synchronization of online and offline channels to ensure a holistic customer experience. The innovation-technological stage includes the extensive implementation of artificial intelligence, AR/VR, blockchain, and emotional analytics. The study draws conclusions about the patterns of transition between stages and the role of innovation in transforming business models in retail. Key directions for further development of marketing innovations are identified, including the technologization of customer experience, intelligent marketing automation, a sustainable approach, Web3 integration, the growth of social commerce, and the use of emotional analytics. However, the implementation of these directions is accompanied by a number of challenges related to the rapid pace of technological change, increasing consumer expectations, and the need to adapt business models to new ethical and environmental standards. In Ukraine, these challenges are further intensified by martial law conditions, market instability, limited resources, and the urgent need for rapid transformation of the retail sector to fit the new realities. It is noted that the development vectors of marketing innovations in retail form a complex yet high-potential system of change that requires strategic thinking, flexibility, and readiness to implement new formats of customer interaction. The article has practical significance for marketing professionals, retail business managers, and researchers working on adapting business practices to the evolving digital economy.
Paper define innovative approach to unify authentication across Web2 and Web3 ecosystems by using biometric-driven decentralized identifiers (DIDs). The framework employs zero-knowledge attestations (ZKPs) to ensure privacy during verification processes [7], [11] and utilizes Chainlink's Cross-Chain protocol related toInteroperability(CCIP) for flawless operation across multiple blockchains [17]. To enhance liveness detection, we incorporate federated learning to eliminate centralized storage of sensitive biometric data [19]. A novel contribution is the Biometric Soulbound Token (BST), a non-transferable NFT that securely stores hashed facial data [5]. Also, quantum-resistant ZKPs are used to verify biometric matches without exposing raw inputs [14]. The DIDs function cohesively across Ethereum, Polygon, and Solana. Experimental results demon- strate a 99.2% authentication accuracy, a 1.3 -second latency, and full compliance with GDPR. By empowering users with control over their biometric data, this framework bridges centralized and decentralized platforms, enabling secure and efficient identity management.
S. Raghavendrachar, Gagan Shivanna, V. Aditya, H. N. Karthik · 5 authors
Financial transparency is a persistent challenge for NGOs, leading to trust issues, inefficiencies, and fund mismanagement. Trust Block is a blockchain-based web application designed to enhance accountability by enabling real-time tracking of donations and fund allocations through Ethereum blockchain, smart contracts, and decentralised ledgers. Built with React.js, Node.js, and MongoDB, and secured using Ganache and Solidity, the system automates financial processes, minimises human intervention, and ensures immutable transaction records. By providing real-time insights to donors and regulatory bodies, Trust Block fosters trust and financial integrity in the NGO sector, demonstrating the power of Web3 technologies in creating secure and transparent transactions.
In the rapidly evolving landscape of digital marketing and electronic commerce, short-form content—particularly on platforms like Twitter (now X)—has become pivotal for real-time branding, community engagement, and product promotion. The rise of Non-Fungible Tokens (NFTs) and Web3 ecosystems further underscores the need for domain-specific, engagement-oriented social media content. However, automating the generation of such content while balancing linguistic quality, semantic relevance, and audience engagement remains a substantial challenge. To address this, we propose RL-TweetGen, a socio-technical framework that integrates instruction-tuned large language models (LLMs) with reinforcement learning (RL) to generate concise, impactful, and engagement-optimized tweets. The framework incorporates a structured pipeline comprising domain-specific data curation, semantic classification, and intent-aware prompt engineering, and leverages Parameter-Efficient Fine-Tuning (PEFT) with LoRA for scalable model adaptation. We fine-tuned and evaluated three LLMs—LLaMA-3.1-8B, Mistral-7B Instruct, and DeepSeek 7B Chat—guided by a hybrid reward function that blends XGBoost-predicted engagement scores with expert-in-the-loop feedback. To enhance lexical diversity and contextual alignment, we implemented advanced decoding strategies, including Tailored Beam Search, Enhanced Top-p Sampling, and Contextual Temperature Scaling. A case study focused on NFT-related tweet generation demonstrated the practical effectiveness of RL-TweetGen. Experimental results showed that Mistral-7B achieved the highest lexical fluency (BLEU: 0.2285), LLaMA-3.1 exhibited superior semantic precision (BERT-F1: 0.8155), while DeepSeek 7B provided balanced performance. Overall, RL-TweetGen presents a scalable and adaptive solution for marketers, content strategists, and Web3 platforms seeking to automate and optimize social media engagement. The framework advances the role of generative AI in digital commerce by aligning content generation with platform dynamics, user preferences, and marketing goals.
This study examines the role of interpersonal communication in disseminating airdrop information as an alternative income source within the Web3 industry, focusing on the CryptoIndo Jogja community. Airdrops, as a method of distributing digital assets without financial investment, are accessible to individuals from diverse backgrounds and depend on reliable information exchange. Using a qualitative descriptive approach, data were collected through in-depth interviews, observations, and documentation. Joseph A. DeVito’s Interpersonal Communication Theory and Ordonez’s Information Dissemination Theory were applied to analyze communication dynamics within the community. Findings show that interpersonal communication in CryptoIndo Jogja is characterized by openness, empathy, supportiveness, and equality, fostering trust and collaborative learning. Members freely share tutorials, insights, and risk considerations related to airdrops through direct discussions, Telegram groups, supported by credible communicators and timely, clear messages. The results indicate that while airdrops are not a primary source of income, they provide supplementary rewards ranging from USD 30 to 500 and improve participants’ understanding of the Web3 ecosystem. This research highlights that effective interpersonal communication, combined with strategic information dissemination, accelerates knowledge sharing, strengthens community engagement, and empowers individuals to access emerging opportunities in the decentralized digital economy. Keywords: Interpersonal Communication, Airdrop, Web3 Community, Information Dissemination
<b>Abstract</b><br>Traditional electoral systems exhibit critical vulnerabilities including vote manipulation, centralized points of failure, and compromised transparency that undermine democratic integrity. This research presents BLOCKELECT, a decentralised blockchain-based secure voting system designed to address these fundamental challenges. The system employs Ethereum smart contracts written in Solidity to enforce immutable voting rules, Web3.js for blockchain integration, and MetaMask wallet authentication for secure voter verification. The proposed architecture implements dual interfaces for voters and electoral commissions, with distributed consensus mechanisms ensuring real-time transaction validation. Smart contracts automatically enforce electoral rules while maintaining cryptographic immutability of all voting transactions. The decentralised design eliminates single points of failure by distributing vote storage and validation across multiple network nodes. System validation employed comprehensive testing including unit, integration, system, and security testing methodologies. Results demonstrate successful prevention of vote tampering, elimination of double voting, and provision of transparent, auditable election results. Implementation utilised Truffle framework, Ganache blockchain simulation, and Node.js back-end services following an Agile Prototype-based Iterative Development methodology. This research demonstrates the feasibility of blockchain technology in creating trustworthy electoral systems, indicating that blockchain-based voting represents a viable solution for enhancing democratic processes while addressing persistent challenges of electoral fraud and lack of public confidence in traditional voting mechanisms.Traditional electoral systems exhibit critical vulnerabilities including vote manipulation, centralized points of failure, and compromised transparency that undermine democratic integrity. This research presents BLOCKELECT, a decentralised blockchain-based secure voting system designed to address these fundamental challenges. The system employs Ethereum smart contracts written in Solidity to enforce immutable voting rules, Web3.js for blockchain integration, and MetaMask wallet authentication for secure voter verification. The proposed architecture implements dual interfaces for voters and electoral commissions, with distributed consensus mechanisms ensuring real-time transaction validation. Smart contracts automatically enforce electoral rules while maintaining cryptographic immutability of all voting transactions. The decentralised design eliminates single points of failure by distributing vote storage and validation across multiple network nodes. System validation employed comprehensive testing including unit, integration, system, and security testing methodologies. Results demonstrate successful prevention of vote tampering, elimination of double voting, and provision of transparent, auditable election results. Implementation utilised Truffle framework, Ganache blockchain simulation, and Node.js back-end services following an Agile Prototype-based Iterative Development methodology. This research demonstrates the feasibility of blockchain technology in creating trustworthy electoral systems, indicating that blockchain-based voting represents a viable solution for enhancing democratic processes while addressing persistent challenges of electoral fraud and lack of public confidence in traditional voting mechanisms.
"With growing concerns about mental well-being, users want efficacious means to monitor emotions and get personalized assistance, with current solutions often sacrificing privacy or offering shallow revelations. ZenLoop overcomes the shortcomings by combining AI-based analysis of emotion with safe Web3 storage to provide both well-being support alongside privacy. This paper builds a conversational AI chatbot that offers coping mechanisms, a mood tracker to record emotion states, and an analysis dashboard to enable users to identify behavior patterns. Developed with React for frontend, Node.js for backend, and MongoDB for organized data, ZenLoop provides empathy-based responses leveraging NLP models trained on mental well-being dialogues. Journals are encrypted and stored in Web3-based storage, with immutable, decentralized protection. Trends in moods are depicted in interactive graphs, and AI-driven insights enable users to monitor emotion shifts. Tests show enhanced user engagement, improved self-perception, along with superior protection of data. The chatbot is effective in detecting levels of distress along with recommended interventions, promoting emotional resilience. By combining AI-driven tools for mental well-being with the security of blockchain, ZenLoop enables users to express emotion securely, monitor their mental well-being patterns, and get personalized advice at no cost of privacy. This work demonstrates the potential of privacy-based AI-based solutions to promote well-being at the emotional level, leading to the development of secure, user-centric applications for mental well-being.
Due to digitalization and AI technology, whole world is moving towards the modernization of all digital applications. As there is a growing demand for conducting elections online to increase voting percentage and reduction in human resource need and time. Till date, India had not conducted any elections online, but there is big necessity to do this digitally as AI World is beginning now. We developed online voting system by adding Rivest Shamir Adleman-Key Encapsulation Mechanism (RSAKEM), Advanced Encryption Standard (AES) with Blockchain technology. The framework used to design a safe, attack proof and translucent methodology which will store user votes in more prominent secured way. Ethereum block chain with Ganache is used for local development to achieve immutability and transparency. Voting process is initialized by written smart contracts based on solidity. Solidity is used for registration of voters and counting of votes. A two factor authentication (2FA) and email verification through one time password (OTP) is used to guarantee the voter identification. Interplanetary file systems (IPFS) are used to store list of voters and votes casted by voters. The registration of voters, choices of ballots and authentication is made so simple. Java spring boot is used to develop backend which was used by Web3j. This backend was used to offer block chain interactions, authentication, and encryption. The framework will be useful for governmental organizations, multinational corporations, Educational institutions and commercial associations for conducting their elections smoothly. These new framework with respect of higher throughput achieved major outcomes with respect to security principles as confidentiality is preserved, integrity is achieved through Metamask and availability is maintained.
By Elizabeth Enkin, University of Nebraska-Lincoln DOI: https://www.doi.org/10.69732/CKTL9913 As language teachers, we are keenly aware of the important benefits that Web 2.0, the collaborative web, has brought to language teaching. From social media to audio and visual tools, Web 2.0
Purpose Web3 technologies are regarded as either tools for enhancing transparency or as mechanisms for delivering tokenised incentives. This study aims to examine how blockchain-enabled transparency builds user trust and how tokenised products convert trust into customer loyalty and improve economic performance. By integrating behavioural, technological and economic perspectives, this study offers a comprehensive framework of how tourism platforms can leverage Web3 technologies to drive user engagement and business value. Design/methodology/approach Three studies were conducted. Firstly, a between-groups experiment was performed to identify the causal effect of Web3-enabled transparency on trust perceptions and adoption intentions among travellers. Secondly, a vector autoregressive model was performed to analyse how trust affects loyalty dynamically over time within blockchain ecosystems. Thirdly, a multivariate ordinary least squares regression model was used to assess the direct effect of customer loyalty on platform performance. Findings Study 1 shows that blockchain-based transparency significantly enhances user trust and encourages platform adoption, supporting the transparency−trust link. Study 2 clarifies the relationship between Web3-enabled trust and customer loyalty. Study 3 confirms a robust relationship between non-fungible tokens (NFT)-based customer loyalty and tangible economic outcomes. Originality/value This study bridges the gap between blockchain transparency and customer trust formation and extends existing knowledge on tokenisation and NFTs within customer loyalty frameworks, which expands the role of customer loyalty as a significant driver of platform-level economic outcomes. These insights offer tourism practitioners guidelines for operationalising Web3 technologies to achieve competitive advantages.
This article explores how the integration of Artificial Intelligence (AI), Machine Learning (ML), Web3.0, Blockchain, Metaverse, and Non-Fungible Tokens (NFTs) will revolutionize various aspects of public life globally over the next decade. We introduce novel perspectives such as AI-driven decentralized governance, blockchain-based universal basic income, and metaverse-enabled global education platforms. These technologies will transform global supply chains through AI-driven forecasting and blockchain-verified logistics, ensuring transparency and efficiency. Healthcare will advance with AI-powered telemedicine and personalized treatments, reducing disparities in underserved regions. Autonomous systems will enhance urban mobility and disaster response, fostering sustainable smart cities. Web3.0 will empower users with decentralized digital identities and data sovereignty, redefining advertising and social media through token-based models. Blockchain will secure academic credentials, streamline insurance, and enable transparent philanthropy, while carbon credit markets promote sustainability. The metaverse will revolutionize remote work, healthcare consultations, and cultural preservation through immersive virtual environments. NFTs will democratize real estate and creative economies, enabling tokenized ownership and secure voting systems. Synergistically, these technologies will create decentralized e-commerce, disaster response systems, and virtual innovation hubs, fostering equitable digital ecosystems. However, challenges like digital divides, AI biases, and blockchain scalability must be addressed to ensure inclusive adoption. This article envisions a future where these advancements redefine governance, economies, and social interactions, paving the way for an innovative, equitable global society. AI-driven avatars and decentralized AI training platforms will further enhance virtual collaboration, while tokenized cultural assets empower communities, ensuring a resilient, inclusive digital future.
The rapid development of large language models (LLMs) has significantly propelled the development of artificial intelligence (AI) agents, which are increasingly evolving into diverse autonomous entities, advancing the LLM-based multi-agent systems (LaMAS). However, current agentic ecosystems remain fragmented and closed. Establishing an interconnected and scalable paradigm for Agentic AI has become a critical prerequisite. Although Agentic Web proposes an open architecture to break the ecosystem barriers, its implementation still faces core challenges such as privacy protection, data management, and value measurement. Existing centralized or semi-centralized paradigms suffer from inherent limitations, making them inadequate for supporting large-scale, heterogeneous, and cross-domain autonomous interactions. To address these challenges, this paper introduces the blockchain-enabled trustworthy Agentic Web (BetaWeb). By leveraging the inherent strengths of blockchain, BetaWeb not only offers a trustworthy and scalable infrastructure for LaMAS but also has the potential to advance the Web paradigm from Web3 (centered on data ownership) towards Web3.5, which emphasizes ownership of agent capabilities and the monetization of intelligence. Beyond a systematic examination of the BetaWeb framework, this paper presents a five-stage evolutionary roadmap, outlining the path of LaMAS from passive execution to advanced collaboration and autonomous governance. We also conduct a comparative analysis of existing products and discuss key challenges of BetaWeb from multiple perspectives. Ultimately, we argue that deep integration between blockchain and LaMAS can lay the foundation for a resilient, trustworthy, and sustainably incentivized digital ecosystem. A summary of the enabling technologies for each stage is available at https://github.com/MatZaharia/BetaWeb.