Research on Tourism Culture Label Identification from the Perspective of Netroots Economy: The case of Liaoning Province

In the winter of 2023, Liaoning Province became the center of a tourism boom in northeastern China, generating unprecedented revenue. This study set out to analyze the digital landscape of social media, specifically mining user-generated content from platforms such as Xiaohongshu and Dianping. Using web crawling techniques, we compiled a rich dataset of textual information, which was then rigorously pre-processed to ensure its purity and relevance. We delved into the core of Liaoning's tourism culture by applying a sophisticated text mining technique, LDA topic modeling, to reveal the nature of its cultural identity. This approach not only reveals the core themes, but also highlights the unique attributes that define Liaoning's tourism appeal. Meanwhile, sentiment analysis was used to interpret the emotional undercurrents in the textual data to reveal tourists' collective feelings toward Liaoning's cultural offerings. We also constructed a semantic network of Liaoning's tourism culture and used semantic network analysis to map the complex relationships among cultural labels. This work aims to provide decision makers in the government and tourism sector with an in-depth understanding and a sound scientific framework of Liaoning's tourism culture. In doing so, it contributes to the sustainable development and protection of Liaoning's tourism industry, ensures the preservation of its cultural heritage, and takes the lead in exploring the potential of text mining in the field of tourism culture, providing new academic perspectives and promoting innovation in the field.