In the 2023 edition of the White Paper on Information and Communications, it is estimated that the population of social networking services in Japan will exceed 100 million by 2022, and the influence of social networking services in Japan is growing significantly. In addition, marketing using SNS and research on the propagation of emotions and information on SNS are being actively conducted, creating the need for a system for predicting trends in SNS interactions. We have already created a system that simulates the behavior of various communities on SNS by building a virtual SNS environment in which agents post and reply to each other in a chat community created by agents using a LLMs. In this paper, we evaluate the impact of the search extension generation mechanism used to create posts and replies in a virtual SNS environment using a simulation system on the ability to generate posts and replies. As a result of the evaluation, we confirmed that the proposed search extension generation mechanism, which mimics human search behavior, generates the most natural exchange.

翻译：在2023年版《信息通信白皮书》中，日本社交网络服务用户规模预计将于2022年突破1亿人次，其社会影响力正显著增强。与此同时，基于社交网络的营销活动及情感信息传播研究日益活跃，亟需建立能够预测社交网络互动趋势的系统。我们已构建了基于大型语言模型的虚拟社交网络环境，通过智能体在聊天社区中相互发帖与回复，实现了多类型社区行为的模拟。本文通过仿真系统评估了虚拟社交网络中用于生成发帖与回复的检索扩展生成机制对内容生成能力的影响。实验结果表明，所提出的模拟人类检索行为的检索扩展生成机制能够产生最自然的对话交互。