In our modern, fast-paced, and interconnected world, the importance of mental well-being has grown into a matter of great urgency. However, traditional methods such as Emotional Support Conversations (ESC) face challenges in effectively addressing a diverse range of individual personalities. In response, we introduce the Social Support Conversation (S2Conv) framework. It comprises a series of support agents and the interpersonal matching mechanism, linking individuals with persona-compatible virtual supporters. Utilizing persona decomposition based on the MBTI (Myers-Briggs Type Indicator), we have created the MBTI-1024 Bank, a group that of virtual characters with distinct profiles. Through improved role-playing prompts with behavior preset and dynamic memory, we facilitate the development of the MBTI-S2Conv dataset, which contains conversations between the characters in the MBTI-1024 Bank. Building upon these foundations, we present CharacterChat, a comprehensive S2Conv system, which includes a conversational model driven by personas and memories, along with an interpersonal matching plugin model that dispatches the optimal supporters from the MBTI-1024 Bank for individuals with specific personas. Empirical results indicate the remarkable efficacy of CharacterChat in providing personalized social support and highlight the substantial advantages derived from interpersonal matching. The source code is available in \url{https://github.com/morecry/CharacterChat}.

翻译：在当今快节奏且高度互联的世界中，心理健康的重要性已变得愈发紧迫。然而，传统方法（如情感支持对话（ESC））在有效应对多样化个体人格方面面临挑战。为此，我们提出社会支持对话（S2Conv）框架。该框架包含一系列支持代理及人际匹配机制，可将个体与人格兼容的虚拟支持者相连接。基于MBTI（迈尔斯-布里格斯类型指标）的人格分解，我们构建了包含1024个具有不同特征虚拟角色的MBTI-1024银行。通过改进的具有行为预设和动态记忆的角色扮演提示，我们推动了MBTI-S2Conv数据集的开发，该数据集包含MBTI-1024银行中角色之间的对话。在此基础上，我们提出了CharacterChat——一个全面的S2Conv系统，包括基于人格与记忆的对话模型，以及用于从MBTI-1024银行中为具有特定人格的个体分配最佳支持者的人际匹配插件模型。实证结果表明，CharacterChat在提供个性化社会支持方面具有显著效能，并突出显示了人际匹配所带来的巨大优势。源代码可在\url{https://github.com/morecry/CharacterChat}获取。