The Backstory to “Swaying the Public”: A Design Chronicle of Election Forecast Visualizations

Fumeng Yang;Mandi Cai;Chloe Mortenson;Hoda Fakhari;Ayse D. Lokmanoglu;Nicholas Diakopoulos;Erik C. Nisbet;Matthew Kay
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Abstract

A year ago, we submitted an IEEE VIS paper entitled “Swaying the Public? Impacts of Election Forecast Visualizations on Emotion, Trust, and Intention in the 2022 U.S. Midterms” [50], which was later bestowed with the honor of a best paper award. Yet, studying such a complex phenomenon required us to explore many more design paths than we could count, and certainly more than we could document in a single paper. This paper, then, is the unwritten prequel—the backstory. It chronicles our journey from a simple idea—to study visualizations for election forecasts—through obstacles such as developing meaningfully different, easy-to-understand forecast visualizations, crafting professional-looking forecasts, and grappling with how to study perceptions of the forecasts before, during, and after the 2022 U.S. midterm elections. This journey yielded a rich set of original knowledge. We formalized a design space for two-party election forecasts, navigating through dimensions like data transformations, visual channels, and types of animated narratives. Through qualitative evaluation of ten representative prototypes with 13 participants, we then identified six core insights into the interpretation of uncertainty visualizations in a U.S. election context. These insights informed our revisions to remove ambiguity in our visual encodings and to prepare a professional-looking forecasting website. As part of this story, we also distilled challenges faced and design lessons learned to inform both designers and practitioners. Ultimately, we hope our methodical approach could inspire others in the community to tackle the hard problems inherent to designing and evaluating visualizations for the general public.
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引导公众 "的背景故事:选举预测可视化设计纪事
一年前,我们提交了一篇题为 "Swaying the Public?选举预测可视化对 2022 年美国中期选举中的情感、信任和意向的影响》[50],这篇论文后来获得了最佳论文奖。然而,要研究如此复杂的现象,我们需要探索的设计路径多得数不清,当然也不是一篇论文所能记录的。因此,这篇论文就是未写的前传--背景故事。它记录了我们从一个简单的想法--研究选举预测的可视化--到克服重重困难的历程,例如开发有意义的不同的、易于理解的预测可视化,制作专业的预测,以及在2022年美国中期选举之前、期间和之后如何研究人们对预测的看法。这一历程产生了丰富的原创知识。我们正式确定了两党选举预测的设计空间,通过数据转换、视觉渠道和动画叙事类型等维度进行导航。通过与 13 位参与者一起对 10 个代表性原型进行定性评估,我们确定了在美国大选背景下解释不确定性可视化的六个核心观点。这些见解为我们的修改提供了依据,从而消除了视觉编码中的模糊性,并制作出了一个看起来很专业的预测网站。作为故事的一部分,我们还提炼了所面临的挑战和设计方面的经验教训,为设计者和从业者提供参考。最终,我们希望我们有条不紊的方法能够激励社区中的其他人解决为公众设计和评估可视化所固有的难题。
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