User Ex Machina：模拟作为人机交互文本分析的设计探针
User Ex Machina : Simulation as a Design Probe in Human-in-the-Loop Text Analytics
摘要：
主题模型是一种被广泛应用的分析技术，用于对文档进行聚类和呈现文本语料库的主题元素。这些模型的优化仍然具有挑战性，并且通常需要一种“人在回路”的方法，即领域专家使用他们的知识来引导和调整。然而，这些模型的脆弱性，不完整性和不透明性意味着即使是微小的变化也可能导致结果模型中出现大的和潜在的不良变化。在本文中，我们进行了以人为中心的互动与主题模型的模拟为基础的分析，与主题模型的敏感性，以常见的用户操作类的目标。我们发现，用户交互的影响，不同的幅度，但往往产生负面影响的方式，用户难以评估的建模质量。我们建议将敏感性和“多元宇宙”分析纳入主题模型界面，以克服这些缺陷。
英文摘要：
Topic models are widely used analysis techniques for clustering documents and surfacing thematic elements of text corpora. These models remain challenging to optimize and often require a "human-in-the-loop" approach where domain experts use their knowledge to steer and adjust. However, the fragility, incompleteness, and opacity of these models means even minor changes could induce large and potentially undesirable changes in resulting model. In this paper we conduct a simulation-based analysis of human-centered interactions with topic models, with the objective of measuring the sensitivity of topic models to common classes of user actions. We find that user interactions have impacts that differ in magnitude but often negatively affect the quality of the resulting modelling in a way that can be difficult for the user to evaluate. We suggest the incorporation of sensitivity and "multiverse" analyses to topic model interfaces to surface and overcome these deficiencies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
