Narrative Character Network Explains Storytelling Success

Narratives are central to human communication and entertainment, yet why some stories captivate audiences better than others remains poorly understood. Building on recent theories that emphasize the interdependence of fictional characters, this study introduces a network-based framework for explaining storytelling success. We conceptualize narratives as networks composed of characters and their interactions and apply large-scale computational analysis to over 10,000 novels and 1,000 movie screenplays. Across these two studies, structural features of the narrative character networks, including lower clustering, shorter path lengths, and higher modularity, explain greater popularity and audience ratings. These findings demonstrate that storytelling success is shaped by how characters are structurally connected and organized. By formalizing story architecture as a measurable network, we provide a scalable framework for advancing media entertainment theory, linking cognitive models of graph learning with the structural organization of stories at scale.