Dissemination Strategies And User Behavior For Jinju Opera On Short-Video Platforms: A Data-Driven Analysis

Abstract

Short-video platforms have emerged as crucial channels for spreading traditional performing arts like Jinju Opera. This study offers a data-driven analysis of how user behavior and dissemination strategies shape the reach and engagement of Jinju Opera content online. Using large-scale data from two leading short-video platforms, we apply an algorithmic framework that clusters viewer retention curves, analyzes user engagement trajectories, and simulates different content dissemination strategies. Specifically, we evaluate modern video editing techniques and influencer (key opinion leader, KOL) seeding as interventions to boost viewer retention and content spread. We identify distinct patterns of audience retention and engagement life-cycles in Jinju Opera videos. Our results show that adapting video editing to the short-video format significantly improves early viewer retention and sharing, while KOL-driven dissemination dramatically amplifies content reach. These findings provide actionable insights for optimizing cultural heritage promotion on short-video platforms and contribute to understanding how traditional arts can flourish in the digital media ecosystem.