数据可视化的方式如何影响和纠正对政治两极分化 (错误) 的看法
JonRobert Tartaglione1, Lee de-Wit1
1University of Cambridge, Cambridge, UK.
The British journal of social psychology
|July 17, 2024
概括
更好的数据可视化可以通过纠正误解来减少政治两极分化. 以视觉形式呈现跨党派态度有助于调节观点,并提高估计政治协议的准确性.
科学领域:
- 社会心理学 社会心理学
- 政治科学 政治科学是指政治学.
- 数据可视化 数据可视化
背景情况:
- 学者认为极化过度估计是一个关键因素.
- 对政治分裂的误解是普遍存在的.
- 需要有效的缓解策略来解决两极分化问题.
研究的目的:
- 调查数据可视化是否可以缓解对两极分化的看法.
- 评估视觉展示模式对估计各方协议的影响.
- 探索数据可视化与政治实用化之间的联系.
主要方法:
- 大规模的国际复制 (N=6603).
- 对跨党派态度的数据可视化模式的实验性操纵.
- 衡量对特定议题和整体党内两极分化的看法.
主要成果:
- 数据呈现方式显著缓和对两极分化的看法.
- 视觉化影响了人们对整体党内两极分化的看法.
- 某些可视化促进了较少的两极分化观点和更准确的对协议的估计.
结论:
- 数据可视化是一种可扩展的策略,用于打击偏振误解.
- 视觉呈现影响政治感知和本质化.
- 有效的数据可视化可以促进更准确的群体间理解.
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