Trust plays a fundamental role in shaping the willingness of users to engage and collaborate with artificial intelligence (AI) systems. Yet, measuring user trust remains challenging due to its complex and dynamic nature. While traditional survey methods provide trust levels for long conversations, they fail to capture its dynamic evolution during ongoing interactions. Here, we present VizTrust, which addresses this challenge by introducing a real-time visual analytics tool that leverages a multi-agent collaboration system to capture and analyze user trust dynamics in human-agent communication. Built on established human-computer trust scales-competence, integrity, benevolence, and predictability-, VizTrust enables stakeholders to observe trust formation as it happens, identify patterns in trust development, and pinpoint specific interaction elements that influence trust. Our tool offers actionable insights into human-agent trust formation and evolution in real time through a dashboard, supporting the design of adaptive conversational agents that responds effectively to user trust signals.

本研究解决了在与人工智能系统交互中，用户信任动态测量的复杂性与挑战。提出的VizTrust工具通过实时可视分析，利用多代理协作系统捕捉和分析人机交互中的信任动态，帮助利益相关者实时观察信任形成及其影响因素，从而为适应性对话代理的设计提供有效的反馈和见解。

VizTrust：捕捉人机交互中用户信任动态的可视分析工具