Visual topics in “Perú, Mucho Gusto” TikTok: a comparative LLM-guided video analysis of official and user-generated content

Guillen N.K.; Turpo H.; Zubieta S.; Velásquez M.D.S.; Murakami K. · International Journal of Event and Festival Management (2026) · DOI: 10.1108/ijefm-01-2026-0002

Resumen

Purpose – This study compares how official and user-generated TikTok videos construct a flagship Peruvian gastronomic fair through divergent visual topics, addressing the quantitative underanalysis of video content in event research. Design/methodology/approach – A corpus of 120 TikTok videos (72 official, 48 user-generated) was analyzed through an large language model (LLM)-guided pipeline transforming videos into textual narratives via frame extraction and AI-assisted description. Latent Dirichlet Allocation identified three visual topics validated through Sentence-BERT embeddings. Term Frequency–Inverse Document Frequency analysis and network mapping revealed lexical and structural divergences between content sources. Findings – The three themes represent distributional emphasis within shared vocabularies about events, rather than discrete categorical boundaries. These emerged representing differential emphases within a shared semantic space: Plating and visual presentation, Professional identity and regional heritage and Spatial branding and performance. Official accounts dominate professional legitimation, emphasizing chefs’ experience and contextualizing heritage. User-generated content dominates spatial and performative documentation, prioritizing venues, pavilions and crowds of visitors. Network analysis reveals that both sources employ radial architecture with divergent centrality allocation: official content integrates professional culinary markers in a centralized manner, while marginalizing spatial elements; user-generated content elevates experiential keywords to nuclear status. Practical implications – Festival organizers might benefit from integrating visitor-prioritized spatial elements into their branding strategies to better reflect experiential priorities. The LLM-guided pipeline serves as a systematic approach to identifying alignment gaps, offering a scalable method for visual content auditing that enhances the reach of traditional manual coding and engagement metrics. Originality/value – This study pioneers LLM-guided video-to-text transformation in event research, validating embedding-based techniques where semantic overlap reflects shared contexts rather than limitations. It proposes “compressed authenticity” where platform affordances produce centro-periferia networks with bounded agency through centrality reallocation. 2026 © Emerald Publishing Limited

Instituciones: Universidad San Ignacio de Loyola