AI 中文总结
研究数据叙事出错问题，引入TIC分类法，综合文献并经对700个真实数据叙事定性标注完善，涵盖六个维度，还提供案例语料库和浏览界面，为诊断问题数据叙事及支持可信数据通信提供结构化视角。
AI 中文摘要
数据叙事日益影响公众认知，但其失败很少只是孤立的事实错误或欺骗性图表。相反，它们通过一个更广泛的意义构建过程出现，在此过程中定量证据转化为主张、表述和论据。虽然先前工作在不同领域研究了这些失败，但学界缺乏一个整体视角来解释这些问题如何产生、传播和加剧。为填补这一空白，我们引入了TIC（数据通信问题分类法），它综合自先前文献，并通过对来自事实核查网站、研究数据集和有争议媒体的700个真实数据叙事进行定性标注来完善。TIC在六个维度——数据、分析、视觉编码、文本、推理和解释——上组织反复出现的故障，并将它们置于一个跨越分析、叙事构建和受众接受的框架内。除了分类法和过程框架，我们还贡献了一个带有编码理由的定性标注案例语料库和一个交互式浏览界面。总体而言，这些贡献为诊断有问题的数据叙事提供了一个结构化视角，并为未来可信数据通信的社会技术支持提供信息。
英文摘要
Data narratives increasingly shape public understanding, but their failures are rarely just isolated factual errors or deceptive charts. Instead, they emerge through a broader meaning-making process in which quantitative evidence is transformed into claims, representations, and arguments. While prior work has examined these failures across disparate fields (e.g., statistics, visualization, and fact-checking), the community lacks a holistic lens to explain how these issues arise, propagate, and compound. To address this gap, we introduce TIC, a Taxonomy of Issues in Data Communication, synthesized from prior literature and refined through the qualitative annotation of 700 real-world data narratives from fact-checking sites, research datasets, and controversial media. TIC organizes recurring breakdowns across six dimensions-data, analysis, visual encoding, text, reasoning, and interpretation-and situates them within a framework spanning analysis, narrative construction, and audience reception. Alongside the taxonomy and process framework, we contribute a qualitatively annotated case corpus with coding justifications and an interactive browsing interface. Collectively, these contributions provide a structured lens for diagnosing problematic data narratives and informing future sociotechnical support for trustworthy data communication.
Comments22 pages, 7 figures, 2 tables
