Constella: Supporting Storywriters' Interconnected Character Creation through LLM-based Multi-Agents
July 08, 2025 Β· Declared Dead Β· π ACM Transactions on Computer-Human Interaction
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Authors
Syemin Park, Soobin Park, Youn-kyung Lim
arXiv ID
2507.05820
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI,
cs.MA
Citations
1
Venue
ACM Transactions on Computer-Human Interaction
Last Checked
4 months ago
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.
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