Harnessing computational techniques to analyze and enhance fandom engagement through interaction ritual chains

Abstract. This study explores the application of Interaction Ritual Chains (IRC) theory and computational techniques to analyze and enhance fandom engagement within the Chinese Australian community. By integrating sentiment analysis, social network analysis, and gender-based language analysis, this research provides a comprehensive understanding of how emotional energy, shared focus, and bodily synchronization contribute to fan interactions. We employ a predictive mathematical model to quantify these IRC components and their impact on engagement, leveraging data mining, natural language processing (NLP), and machine learning. The findings reveal the dynamics of fan behavior and offer insights into personalized content recommendations, gamification, and virtual reality experiences to foster deeper emotional bonds and sustained engagement. This study bridges the gap between theoretical frameworks and practical applications, providing a robust foundation for future research on digital fandoms.