<![CDATA[In the digital era, tourists share their travel experiences through social media, generating digital footprints. These footprints provide a valuable source of data for exploring tourists experiences spontaneously, including at cultural heritage sites such as Prambanan Temple. This study analyzed the digital footprint of tourist from TripAdvisor's User Generated Content (UGC) data source. Natural Language Processing (NLP) based on Large Language Models (LLMs) is used to process the comments of tourists left on the source of the Prambanan Temple's virtual space. The Theory of Experience Economics is used to analyze experiences based on the passive and active dimensions of tourist. These findings suggest that LLMs effectively identifies the dimension of the tourist experience at Prambanan Temple, where passive experiences are visual elements such as architectural beauty and landscapes, while active experiences through educational involvement. These findings demonstrate the capacity of LLMs to extract textual meaning from large-scale textual data in complex cultural contexts, contributing new insights to the study of digital tourist behaviors.]]>
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