Zakat in metaverse? Evidence from cyberspace

Purpose This study aims to explore the recent state of zakat metaverse innovation from unstructured data available in cyberspace, i.e. YouTube, Instagram, X (Twitter), Facebook, LinkedIn and Google. Design/methodology/approach This study used “zakat metaverse” keywords to harvest unstructured data and analysed using a mixed-method approach. First step of the analysis applied quantitative text analytics via machine learning tool, followed by the final step of qualitative inductive analysis. Findings Quantitative text analytics identified keywords related to zakat metaverse innovation, whereas qualitative analysis explored the critical insights behind those keywords, presented in thematic interpretation. Research limitations/implications This study only used unstructured internet data, in which other relevant information may not be covered. Practical implications Shariah evaluation of zakat obligations from virtual assets requires the relevantisation of fiqh (Islamic jurisprudence) zakat, which opens future debates. Social implications Many zakat institutions operate in emerging economies where digital poverty occurs, and such zakat metaverse innovation would potentially contribute to this digital divide. The relevance of such innovation becomes a major question regarding its inclusivity. Originality/value This study combines machine learning analytics and qualitative analysis to explore the recent state of metaverse innovation in zakat administration.