Post-covid China's Tourism Image Projection through Instagram: A Mixed Method Based on Image Tagging

This study addresses the post-pandemic challenges faced by China's tourism industry, particularly focusing on the international image projected through Instagram. Utilizing machine learning-based image tagging techniques combined with Peircean semiotic theory, the study conducts a comprehensive quantitative and qualitative analysis of Instagram photos. The research identifies four key themes in China's tourism imagery: Urban Life, Natural Landscapes, Defense and Technology, and Cultural Activities. The theme of Urban Life highlights the dynamic and resilient nature of Chinese cities, with a particular emphasis on Shanghai. Natural Landscapes showcase China's commitment to ecological conservation and sustainable tourism. Defense and Technology focus on advancements in infrastructure, aerospace, and defense, reflecting national pride and technological prowess. Cultural Activities portray the rich cultural tapestry of China, emphasizing festivals and traditional attire. The findings underscore the critical role of visual content in shaping public perceptions of tourism destinations. By systematically analyzing and interpreting large-scale visual data, this study provides DMOs with valuable insights into effective image projection strategies. This research not only contributes to the theoretical understanding of tourism image construction but also offers practical implications for enhancing the global competitiveness of tourism destinations in the post-pandemic era. The innovative combination of machine learning and semiotic analysis represents a significant advancement in the methodological approaches to tourism image research.