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.

通过故事讲述和大型语言模型的整合，我们开发出适用于社区环境下引人入胜且可信的社交机器人。我们引入了故事讲述社交机器人以及故事工程的概念，将虚构游戏角色转变为 “真实” 的社交实体，在玩家社群中与人们相互交互。通过使用 GPT-3 驱动我们的 SSC 原型 “David” 和 “Catherine”，并在 Discord 上的在线游戏社区 “DE (Alias)” 评估它们的表现，我们运用问卷（N=15）和访谈（N=8）对社区成员进行混合方法分析，结果显示故事讲述在社区环境中显著提升了社交机器人的吸引力和可信度。