Fictional Worlds, Real Connections: Developing Community Storytelling Social Chatbots through LLMs
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Abstract (arXiv)
We address the integration of storytelling and Large Language Models (LLMs) to develop engaging and believable Social Chatbots (SCs) in community settings. Motivated by the potential of fictional characters to enhance social interactions, we introduce Storytelling Social Chatbots (SSCs) and the concept of story engineering to transform fictional game characters into "live" social entities within player communities. Our story engineering process includes three steps: (1) Character and story creation, defining the SC's personality and worldview, (2) Presenting Live Stories to the Community, allowing the SC to recount challenges and seek suggestions, and (3) Communication with community members, enabling interaction between the SC and users. We employed the LLM GPT-3 to drive our SSC prototypes, "David" and "Catherine," and evaluated their performance in an online gaming community, "DE (Alias)," on Discord. Our mixed-method analysis, based on questionnaires (N=15) and interviews (N=8) with community members, reveals that storytelling significantly enhances the engagement and believability of SCs in community settings.
Key facts. Cited by 2 papers in the map (data through 13 Oct 2026). Builds on 5 of its 25 references that are in the map. First posted on arXiv 20 Sep 2023.
Builds on
5 of 25 references.
References · 5
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,107
- 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,541
- 2019How should my chatbot interact? A survey on human-chatbot interaction designcited by 56
- 2022StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvementcited by 37
- 2022CodeToon: Story Ideation, Auto Comic Generation, and Structure Mapping for Code-Driven Storytellingcited by 14
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Citing papers per year: 2024: 1; 2025: 1.
2 papers.