负投票以去极化政治
Negative votes to depolarize politics
AI总结：
针对政治极化问题，提出一种允许选民表达负面偏好的投票方案，通过权衡受欢迎度与极化度选出获胜者，以抑制分裂性言论并促进第三方候选人。
摘要：
围绕2020年美国总统选举的争议无疑对当前投票系统在代表人民意愿方面的效率提出了严重关切。在极端两极化的政治环境中，简单的多数投票制（Plurality voting）是否合适？替代性投票方案正逐渐获得公众支持，其中选民对选择进行排序，而不仅仅是投票给他们的首选。然而，这些方案并未捕捉选民偏好的某些关键方面，如对候选人的反对和负面情绪。我认为，这些未表达的负面情绪是政治两极化的主要来源。我提出了一种投票方案，明确表达这些负面偏好，从而可以同时解读每位候选人的受欢迎程度和两极分化程度。获胜者通过在最受欢迎和最少两极分化的候选人之间进行最优权衡来选出。通过惩罚候选人的两极分化行为，我们可以阻止分裂性的竞选言论，并为潜在的第三方候选人铺平道路。
英文摘要：
The controversies around the 2020 US presidential elections certainly casts serious concerns on the efficiency of the current voting system in representing the people's will. Is the naive Plurality voting suitable in an extremely polarized political environment? Alternate voting schemes are gradually gaining public support, wherein the voters rank their choices instead of just voting for their first preference. However they do not capture certain crucial aspects of voter preferences like disapprovals and negativities against candidates. I argue that these unexpressed negativities are the predominant source of polarization in politics. I propose a voting scheme with an explicit expression of these negative preferences, so that we can simultaneously decipher the popularity as well as the polarity of each candidate. The winner is picked by an optimal tradeoff between the most popular and the least polarizing candidate. By penalizing the candidates for their polarization, we can discourage the divisive campaign rhetorics and pave way for potential third party candidates.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
