Navigating large-scale online discussions is difficult due to the rapid pace and large volume of user-generated content. Prior work in CSCW has shown that moderators often struggle to follow multiple simultaneous discussions, track evolving conversations, and maintain contextual understanding--all of which hinder timely and effective moderation. While platforms like Reddit use threaded structures to organize discourse, deeply nested threads can still obscure discussions and make it difficult to grasp the overall trajectory of conversations. In this paper, we present an interactive system called Needle to support better navigation and comprehension of complex discourse within threaded discussions. Needle uses visual analytics to summarize key conversational metrics--such as activity, toxicity levels, and voting trends--over time, offering both high-level insights and detailed breakdowns of discussion threads. Through a user study with ten Reddit moderators, we find that Needle supports moderation by reducing cognitive load in making sense of large discussion, helping prioritize areas that need attention, and providing decision-making supports. Based on our findings, we provide a set of design guidelines to inform future visualization-driven moderation tools and sociotechnical systems. To the best of our knowledge, Needle is one of the first systems to combine interactive visual analytics with human-in-the-loop moderation for threaded online discussions.

翻译：由于用户生成内容更新迅速且体量庞大，大规模在线讨论的导航十分困难。计算机支持协同工作（CSCW）领域的先前研究表明，版主常常难以同时追踪多个并行讨论、跟进持续演变的对话并维持上下文理解——这些因素均会阻碍及时有效的社区管理。尽管Reddit等平台采用线程化结构组织讨论，但深度嵌套的线程仍可能掩盖讨论脉络，使用户难以把握对话的整体走向。本文提出一种名为Needle的交互式系统，旨在支持对线程化讨论中复杂话语的导航与理解。Needle运用可视化分析技术，随时间维度汇总关键对话指标（如活跃度、毒性水平与投票趋势），既提供高层级洞察，也支持讨论线程的细粒度解析。通过对十位Reddit版主开展用户研究，我们发现Needle通过降低理解大规模讨论的认知负荷、辅助确定需优先关注的区域并提供决策支持，有效提升了社区管理效能。基于研究结果，我们提出一套设计准则，为未来可视化驱动的社区管理工具及社会技术系统提供参考。据我们所知，Needle是首个将交互式可视化分析与人在回路的社区管理模式相结合，专门用于线程化在线讨论的系统。