Partisanship Meets Social Networks: How Politically Heterogeneous Acquaintances and Close Relationships Buffer Partisan Animosity

IF 2.7 2区 社会学 Q1 SOCIOLOGY
Delia Baldassarri, Jona de Jong
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引用次数: 0

Abstract

Politically heterogeneous social networks have long been considered as a safeguard against political division. However, in today’s polarized political climate, the effectiveness of cross-partisan interactions in mitigating animosity is increasingly questioned. Prior research emphasizes the importance of hearing-the-other-side through cross-partisan discussions with close ties. We confirm that these discussions still take place and are related to lower inter-partisan animosity. Moreover, we propose a complementary mechanism, seeing-the-other-side, according to which even brief interactions with out-partisan acquaintances serve to reduce distorted views of out-partisans, thereby lowering inter-partisan hostility. Using original data from the United States, we find that both close tie and acquaintance networks display significant political heterogeneity and this heterogeneity is associated with lower partisan animosity. Experimentally, we show that reducing misperceptions by increasing the salience of similarities between in-partisan and out-partisan acquaintances further reduces hostility. These findings highlight the continued relevance of everyday political diversity in tempering partisan divisions and nuance worries about partisan echo chambers.
党派关系遇到社会网络:政治上异质的熟人和亲密关系如何缓冲党派仇恨
长期以来,政治异质性社会网络一直被视为防止政治分裂的保障。然而,在当今两极分化的政治气候下,跨党派互动在缓解敌意方面的有效性日益受到质疑。先前的研究强调通过密切联系的跨党派讨论听取对方意见的重要性。我们确认,这些讨论仍在进行,并与党派间敌意的降低有关。此外,我们提出了一种互补机制,即看到另一面,根据该机制,即使与党派外的熟人进行短暂的互动,也有助于减少对党派外人士的扭曲看法,从而降低党派间的敌意。使用来自美国的原始数据,我们发现亲密关系和熟人网络都表现出显著的政治异质性,这种异质性与较低的党派仇恨有关。实验表明,通过增加党派内和党派外熟人之间相似性的显著性来减少误解,进一步减少敌意。这些发现强调了日常政治多样性在缓和党派分歧和细微差别对党派回声室的担忧方面的持续相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Sociological Science
Sociological Science Social Sciences-Social Sciences (all)
CiteScore
4.90
自引率
2.90%
发文量
13
审稿时长
6 weeks
期刊介绍: Sociological Science is an open-access, online, peer-reviewed, international journal for social scientists committed to advancing a general understanding of social processes. Sociological Science welcomes original research and commentary from all subfields of sociology, and does not privilege any particular theoretical or methodological approach.
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