MetaHate: AI‐based hate speech detection for secured online gaming in metaverse using blockchain

IF 1.5 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Security and Privacy Pub Date : 2023-09-13 DOI:10.1002/spy2.343
Harshil Sanghvi, Rushir Bhavsar, Vini Hundlani, Lata Gohil, Tarjni Vyas, Anuja Nair, Shivani Desai, Nilesh Kumar Jadav, Sudeep Tanwar, Ravi Sharma, Nagendar Yamsani
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Abstract

The emergence of Web 3.0, blockchain technology (BC), and artificial intelligence (AI) are transforming multiplayer online gaming in the metaverse. This development has its concerns about safety and inclusivity. Hate speech, in particular, poses a significant threat to the harmony of these online communities. Traditional moderation methods struggle to cope with the immense volume of user‐generated content, necessitating innovative solutions. This article proposes a novel framework, MetaHate, that employs AI and BC to detect and combat hate speech in online gaming environments within the metaverse. Various machine learning (ML) models are applied to analyze Hindi–English code mixed datasets, with gradient boosting proving the most effective, achieving 86.01% accuracy. AI algorithms are instrumental in identifying harmful language patterns, while BC technology ensures transparency and user accountability. Moreover, a BC‐based smart contract is proposed to support the moderation of hate speech in the game chat. Integrating AI and BC can significantly enhance the safety and inclusivity of the metaverse, underscoring the importance of these technologies in the ongoing battle against hate speech and in bolstering user engagement. This research emphasizes the potential of AI and BC synergy in creating a safer metaverse, highlighting the need for continuous refinement and deployment of these technologies.
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MetaHate:基于AI的仇恨言论检测,用于使用区块链在元宇宙中安全的在线游戏
Web 3.0、区块链技术(BC)和人工智能(AI)的出现正在改变虚拟世界中的多人在线游戏。这种发展有其对安全性和包容性的担忧。尤其是仇恨言论,对这些网络社区的和谐构成了重大威胁。传统的审核方法难以应对大量用户生成的内容,因此需要创新的解决方案。本文提出了一个新的框架,MetaHate,它使用AI和BC来检测和打击虚拟世界中在线游戏环境中的仇恨言论。应用各种机器学习(ML)模型分析印地语-英语代码混合数据集,其中梯度增强被证明是最有效的,达到86.01%的准确率。人工智能算法有助于识别有害的语言模式,而BC技术确保了透明度和用户问责制。此外,提出了一个基于BC的智能合约来支持游戏聊天中的仇恨言论的调节。整合人工智能和BC可以显着增强虚拟世界的安全性和包容性,强调这些技术在持续打击仇恨言论和增强用户参与度方面的重要性。这项研究强调了人工智能和BC协同创造更安全的元宇宙的潜力,强调了持续改进和部署这些技术的必要性。
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