Constella: Supporting Storywriters' Interconnected Character Creation through LLM-based Multi-Agents

TL;DR

Constella is an LLM-based multi-agent tool that aids storywriters in creating interconnected characters by suggesting related characters, revealing their inner thoughts, and manifesting relationships, thereby enhancing character development and relational understanding.

Contribution

This paper introduces Constella, a novel multi-agent system that supports interconnected character creation, addressing writers' challenges in envisioning and fleshing out relational dynamics.

Findings

Enabled creation of expansive character communities

Facilitated comparison of characters' thoughts and emotions

Deepened understanding of character relationships

Abstract

Creating a cast of characters by attending to their relational dynamics is a critical aspect of most long-form storywriting. However, our formative study (N=14) reveals that writers struggle to envision new characters that could influence existing ones, balance similarities and differences among characters, and intricately flesh out their relationships. Based on these observations, we designed Constella, an LLM-based multi-agent tool that supports storywriters' interconnected character creation process. Constella suggests related characters (FRIENDS DISCOVERY feature), reveals the inner mindscapes of several characters simultaneously (JOURNALS feature), and manifests relationships through inter-character responses (COMMENTS feature). Our 7-8 day deployment study with storywriters (N=11) shows that Constella enabled the creation of expansive communities composed of related characters, facilitated the comparison of characters' thoughts and emotions, and deepened writers' understanding of character relationships. We conclude by discussing how multi-agent interactions can help distribute writers' attention and effort across the character cast.