Ward George, Schwartz H Andrew, Giorgi Salvatore, Menges Jochen I, Matz Sandra C
Department of Economics, University of Oxford.
Department of Computer Science, Stony Brook University.
Am Psychol. 2025 Apr;80(3):323-344. doi: 10.1037/amp0001326. Epub 2024 Jul 25.
Support for populism has grown substantially during the past 2 decades, a development that has coincided with a marked increase in the experience of negative affect around the world. We use a multimodal, multimethod empirical approach, with data from a diverse set of geographical and political contexts, to investigate the extent to which the rising electoral demand for populism can be explained by negative affect. We demonstrate that negative affect-measured via (a) self-reported emotions in surveys as well as (b) automated text analyses of Twitter data-predicts individual-level populist attitudes in two global surveys (Studies 1a and 1b), longitudinal changes in populist party vote shares at general elections in Europe (Study 2), district-level Brexit voting in the 2016 U.K. referendum (Study 3), and county-level vote shares for Donald Trump in the 2016 and 2020 U.S. presidential elections (Studies 4a and 4b). We find that negative emotions-such as fear and anger as well as more often overlooked low-arousal negative emotions like depression and sadness-are predictive of populist beliefs as well as voting and election results at scale. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
在过去20年里，对民粹主义的支持大幅增加，这一发展与全球范围内负面情绪体验的显著上升同时出现。我们采用多模态、多方法的实证方法，利用来自不同地理和政治背景的数据集，来研究对民粹主义不断上升的选举需求在多大程度上可以用负面情绪来解释。我们证明，通过（a）调查中的自我报告情绪以及（b）对推特数据的自动文本分析来衡量的负面情绪，在两项全球调查（研究1a和1b）中预测了个人层面的民粹主义态度，在欧洲大选中民粹主义政党选票份额的纵向变化（研究2）、2016年英国脱欧公投中地区层面的投票情况（研究3）以及2016年和2020年美国总统大选中唐纳德·特朗普在县级的选票份额（研究4a和4b）。我们发现，负面情绪——如恐惧和愤怒，以及更常被忽视的低唤醒负面情绪，如抑郁和悲伤——在大规模上预测了民粹主义信念以及投票和选举结果。（PsycInfo数据库记录（c）2025美国心理学会，保留所有权利）
