论文标题
使用2022年法国和巴西总统选举的在线参与数据了解政治分歧
Understanding Political Divisiveness using Online Participation data from the 2022 French and Brazilian Presidential Elections
论文作者
论文摘要
数字技术可以通过促进详细的政治偏好的表达来增强公民参与。但是，数字参与工作通常依赖于针对涉及一些候选人的选举进行了优化的方法。在这里，我们介绍了在一个在线实验中收集的数据，参与者通过结合2022年法国和巴西总统选举的候选人提出的政策来构建个性化的政府计划。我们使用这些数据来探索汇总社会选择理论中使用的数据，发现与传统聚合功能不相关的分裂度量指标可以识别两极分化的建议。这些指标为每个提案的分裂提供了一个分数，如果没有参与者人口特征的数据，可以估计，并解释了将人口划分的问题。这些发现表明，分裂指标可以是直接数字参与形式的传统聚合功能的有用补充。
Digital technologies can augment civic participation by facilitating the expression of detailed political preferences. Yet, digital participation efforts often rely on methods optimized for elections involving a few candidates. Here we present data collected in an online experiment where participants built personalized government programs by combining policies proposed by the candidates of the 2022 French and Brazilian presidential elections. We use this data to explore aggregates complementing those used in social choice theory, finding that a metric of divisiveness, which is uncorrelated with traditional aggregation functions, can identify polarizing proposals. These metrics provide a score for the divisiveness of each proposal that can be estimated in the absence of data on the demographic characteristics of participants and that explains the issues that divide a population. These findings suggest divisiveness metrics can be useful complements to traditional aggregation functions in direct forms of digital participation.
