Managing Social Interactions on Two-Sided Platforms: Streamer Fatigue in Live Streaming

Featuring synchronous interaction between content creators and audiences, the live-streaming industry has seen remarkable growth. While previous research has underscored the positive effects of audience engagement, the costs associated with such interactions and potential negative effects have received less attention. In this paper, we employ a heterogeneous Hidden Markov Model to quantify the dynamics of streamers’ interaction effort decisions with data from Twitch.com. Our findings suggest that streamers strategically navigate the balance between high interaction levels and potential fatigue. We identify two streamers’ hidden mental states characterized by reduced responsiveness to viewer chats. We find that higher interaction efforts facilitate transitions from the normal to the exhaustion state. Streamers with fewer loyal community members and those with lower status on the platform suffer stronger exhaustion effect from social interactions. This study provides practical recommendations for digital platforms to acknowledge the efforts and challenges faced by content creators.