IEEE Trans Vis Comput Graph. 2018 Jan;24(1):760-769. doi: 10.1109/TVCG.2017.2745240. Epub 2017 Aug 29.
In addition to visualizing input data, interactive visualizations have the potential to be social artifacts that reveal other people's perspectives on the data. However, how such social information embedded in a visualization impacts a viewer's interpretation of the data remains unknown. Inspired by recent interactive visualizations that display people's expectations of data against the data, we conducted a controlled experiment to evaluate the effect of showing social information in the form of other people's expectations on people's ability to recall the data, the degree to which they adjust their expectations to align with the data, and their trust in the accuracy of the data. We found that social information that exhibits a high degree of consensus lead participants to recall the data more accurately relative to participants who were exposed to the data alone. Additionally, participants trusted the accuracy of the data less and were more likely to maintain their initial expectations when other people's expectations aligned with their own initial expectations but not with the data. We conclude by characterizing the design space for visualizing others' expectations alongside data.
除了可视化输入数据外，交互式可视化还具有成为揭示其他人对数据观点的社会人工制品的潜力。然而，嵌入在可视化中的此类社会信息如何影响观察者对数据的解释尚不清楚。受最近展示人们对数据的期望与数据相对比的交互式可视化的启发，我们进行了一项对照实验，以评估以其他人的期望形式展示社会信息对人们回忆数据的能力、他们调整期望以与数据保持一致的程度以及他们对数据准确性的信任度的影响。我们发现，表现出高度一致性的社会信息使参与者相对于仅暴露于数据的参与者更准确地回忆数据。此外，当其他人的期望与他们自己的初始期望一致但与数据不一致时，参与者对数据的准确性信任度降低，并且更有可能保持他们的初始期望。我们最后通过描绘与数据一起可视化其他人期望的设计空间来得出结论。
