The COVID-19 pandemic has changed the research agendas of most scientific communities, resulting in an overwhelming production of research articles in a variety of domains, including medicine, virology, epidemiology, economy, psychology, and so on. Several open-access corpora and literature hubs were established; among them, the COVID-19 Open Research Dataset (CORD-19) has systematically gathered scientific contributions for 2.5 years, by collecting and indexing over one million articles. Here, we present the CORD-19 Topic Visualizer (CORToViz), a method and associated visualization tool for inspecting the CORD-19 textual corpus of scientific abstracts. Our method is based upon a careful selection of up-to-date technologies (including large language models), resulting in an architecture for clustering articles along orthogonal dimensions and extraction techniques for temporal topic mining. Topic inspection is supported by an interactive dashboard, providing fast, one-click visualization of topic contents as word clouds and topic trends as time series, equipped with easy-to-drive statistical testing for analyzing the significance of topic emergence along arbitrarily selected time windows. The processes of data preparation and results visualization are completely general and virtually applicable to any corpus of textual documents - thus suited for effective adaptation to other contexts.

翻译：COVID-19大流行改变了大多数科学领域的研究议程，导致医学、病毒学、流行病学、经济学、心理学等多个领域涌现出大量研究论文。研究人员建立了多个开放获取语料库和文献枢纽，其中COVID-19开放研究数据集（CORD-19）通过收集和索引超过一百万篇论文，系统性地汇总了两年半的科研成果。本文提出CORD-19主题可视化工具（CORToViz），这是一种用于分析CORD-19科学摘要文本语料库的方法及配套可视化工具。该方法基于对前沿技术（包括大语言模型）的审慎筛选，构建了沿正交维度对论文进行聚类的架构，并实现了时序主题挖掘的抽取技术。我们通过交互式仪表板支持主题分析，提供快速一键式可视化功能，以词云形式呈现主题内容，以时间序列形式展示主题演化趋势，并配备易于操作的统计检验工具，用于分析任意选定时间窗口内主题涌现的显著性。数据准备和结果可视化的流程完全通用，可实际应用于任何文本语料库，因此能够有效适配至其他应用场景。