This project differentiates between communication that praises one's political in-group (in-group praise), attacks the opposition (out-group derogation), or focuses on policy details (evidence based), testing their effects on network and attitude polarization. We begin with an agent-based model, which shows that congenial evidence-based exchanges polarize the network and the inclusion of identity-driven communications leads to greater polarization. Once out-group derogation reaches a certain threshold, the network of agents splits into two groups, yet the polarizing effects of in-group praise are yet stronger and emerge more rapidly (i.e., a lower threshold of in-group praise is needed to polarize the network). Using an experimental design on a sample of American partisans, we offer a partial validation of the model. In-group praise and out-group derogation polarize attitudes more than balanced evidence-based news, but not more than congenial evidence-based news. Identity-driven news also has no effects on affective polarization. This multidisciplinary evidence shows that the nature of political content matters.

该项目区分称赞一个人在政治上的团体内（团体内的赞美），攻击反对派（团体外的克减）或侧重于政策细节（基于证据的交流）之间的区别），测试它们对网络和态度极化的影响。我们从基于代理的模型开始，该模型表明基于相近证据的交换使网络极化，而包含身份驱动的通信则导致更大的极化。一旦群体外克减达到一定的阈值，代理人网络就会分为两组，但是群体内表扬的极化作用仍然更强并且更快地出现（即，需要群体内表扬的较低阈值来极化）网络）。通过对美国游击队员的样本进行实验设计，我们对模型进行了部分验证。组内表扬和组外克减使态度比平衡的基于证据的新闻更能使人两极化，但与相投的基于证据的新闻相比则更能使态度两极化。身份驱动的新闻对情感两极分化也没有影响。