Can Data Visualizations Change Minds? Identifying Mechanisms of Elaborative Thinking and Persuasion

D. Markant, Milad Rogha, Alireza Karduni, Ryan Wesslen, Wenwen Dou
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引用次数: 2

Abstract

Recent years have seen rapid growth in data-driven communication and the public availability of datasets on a broad set of social issues. Yet despite this unprecedented accessibility, the public often remains divided along partisan or ideological lines and to lack a common understanding of the issues at stake. In this paper we consider the role of data visualizations in communicating scientific evidence, and in particular, their power to persuade in the face of conflicting prior beliefs and attitudes. We describe a recent study showing that strong attitudes about politically polarized topics were associated with less belief change when interacting with statistical data visualizations. Moreover, there was little evidence for attitude change even when people updated their beliefs about specific empirical relationships. We then draw on research in cognitive science to identify elements of visualizations that may produce such attitude change because they encourage elaborative thinking when interacting with data. We argue for further research that considers how broader attitudes-which are tied to social identity, values, and worldviews-affect the power of data visualizations to persuade among communities with diverse ideological and cultural backgrounds.
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数据可视化能改变人们的想法吗?阐述思维与说服的识别机制
近年来,数据驱动的通信和广泛的社会问题的数据集的公共可用性迅速增长。然而,尽管有这种前所未有的可接近性,公众仍然经常因党派或意识形态而分裂,对利害攸关的问题缺乏共同的理解。在本文中,我们考虑了数据可视化在传播科学证据中的作用,特别是它们在面对相互冲突的先前信念和态度时的说服能力。我们描述了最近的一项研究表明,当与统计数据可视化交互时,对政治两极分化话题的强烈态度与较少的信念变化相关。此外,即使人们更新了他们对具体经验关系的看法,也几乎没有证据表明态度会发生变化。然后,我们利用认知科学的研究来确定可能产生这种态度变化的可视化元素,因为它们在与数据交互时鼓励详细思考。我们主张进行进一步的研究,考虑与社会身份、价值观和世界观相关的更广泛的态度如何影响数据可视化在具有不同意识形态和文化背景的社区中的说服力。
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