01701nas a2200121   4500000000100000008004100001100001300042700001500055700001700070245009900087856015100186520124200337                                       d1 aJian Luo1 aZongwei Hu1 aAliana Leong00aExploring the experience attributes of intangible cultural heritage through big data analytics  uhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-105000687785&doi=10.1177%2f13567667251323644&partnerID=40&md5=fc546a24c225cc8488ad4cd7d05b41763 aIntangible cultural heritage, such as flamenco, renders destination marketing distinctive and enhances individuals’ psychological and physical attachment to the destination. Consequently, understanding the experiential attributes of intangible cultural heritage is essential. Although numerous studies have examined the empirical properties of intangible cultural heritage, user-generated content, often referred to as ‘collective intelligence,’ has not been utilized to investigate these properties. This study analyzed user-generated content through Latent Dirichlet allocation to identify nine experiential attributes of intangible cultural heritage. Drawing on social identity theory, this study examined the heterogeneity of intangible cultural heritage experience attributes among domestic and international tourists. Furthermore, this study investigated the heterogeneity of experiential attributes through emotional analysis and the correlation between these attributes and satisfaction. The results integrate social identity theory into the domain of intangible cultural heritage tourism, offering new insights into experiential attributes and contributing to both theoretical and practical implications within this field.