User Influence, Hashtag Trends, and Engagement Patterns: Analyzing Social Media Network Dynamics in Tourism Using Graph Analytics

This study analyses social media networks in tourism using graphs focusing on user influence, hashtag patterns, and engagement. This study aims to reveal the structural function of core users, development of hashtags, and interaction patterns that construct tourism discourses. Using NodeXL 2024 for social network visualization and clustering analysis, this study measures centrality, modularity, and geodesic distances for influential user detection, topical dissemination, and engagement pattern identification. The results uncover bridging nodes between different communities, the proliferation of thematic hashtags related to sustainability and cultural heritage, and the role of emotional and visual storytelling in the use of engagement patterns. The theoretical implications also progress SNA application in tourism studies by illuminating aspects of how online discourses coalesce and the effect of SNA on access. In practical terms, this study indicates that destination marketers must consider leveraging key influencers, using strategic types of hashtags, and by monitoring engagement at key times to maximize effective destination marketing and to enhance crisis communication. These contributions notwithstanding, limitations involve the omission of sentiment analysis and the necessity for longitudinal data. By exploring new emerging platforms like TikTok and Instagram, researchers can begin to understand the more relevant trends of digital engagement. The present research offers a data-driven approach for facilitating the significance of integrating social media strategies with network externalities for tourism operators.