在预测美国投票结果时,物理的党派亲密度超过了在线联系
Marco Tonin1,2, Bruno Lepri2, Michele Tizzoni1
1Department of Sociology and Social Research, University of Trento, Via Verdi 26, Trento I-38122, Italy.
PNAS nexus
|October 23, 2025
概括
线下社交网络和物理同位模式是美国选举结果的更强有力的预测因素,而不是在线互动. 这项研究强调了物理空间在塑造政治行为和党派隔离方面的关键作用.
科学领域:
- 社会科学 社会科学 社会科学
- 政治科学 政治科学是指政治学.
- 计算社会科学 计算社会科学
背景情况:
- 情感极化和社会分裂影响信息传播和政治结果.
- 了解在线和离线空间中的党派曝光对于分析社会和选举分歧至关重要.
研究的目的:
- 为了比较线下 (物理共同位置,个人线下联系) 与线上 (在线网络,住宅暴露) 党派暴露在美国投票选择中的预测能力.
- 估计和分析县级党派隔离及其与人口和社会经济特征的关联.
主要方法:
- 利用个人调查数据与聚合,非识别的同位点和在线网络数据相结合.
- 采用各种统计建模方法来分析党派曝光,隔离和选举结果之间的关系.
- 专注于美国县和大都会地区的分析.
主要成果:
- 在物理空间 (共同位置) 中的党派曝光比在线或住宅曝光更准确地预测了美国县的选举结果.
- 个人线下社交关系比在线联系更好地预测投票选择.
- 线下党派隔离,由实体遭遇和住宅分类驱动,比在线隔离更广泛,并与教育程度有关.
结论:
- 物理空间和线下社交网络在政治行为和选举结果中扮演的角色比人们通常认为的更为重要.
- 调查结果强调了在研究社交网络对选举的影响时考虑线下互动的重要性,与对线上平台的关注形成鲜明对比.
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