Multilayer Network Model of Movie Script
This work provides a more detailed analysis tool for movie scripts, though it is incremental by extending single-layer network models to multiple layers.
The authors tackled the problem of modeling movie narratives by introducing a multilayer network that captures characters, locations, and other semantic elements from scripts, enabling new measures and insights, as demonstrated on two popular movies.
Network models have been increasingly used in the past years to support summarization and analysis of narratives, such as famous TV series, books and news. Inspired by social network analysis, most of these models focus on the characters at play. The network model well captures all characters interactions, giving a broad picture of the narration's content. A few works went beyond by introducing additional semantic elements, always captured in a single layer network. In contrast, we introduce in this work a multilayer network model to capture more elements of the narration of a movie from its script: people, locations, and other semantic elements. This model enables new measures and insights on movies. We demonstrate this model on two very popular movies.