论文标题
社交网络，确认偏见和震惊选举
Social networks, confirmation bias and shock elections
论文作者
论文摘要
近年来，在线社交网络在政治运动中变得越来越重要，同时，几个国家经历了震惊的选举结果。本文提出了将这两个现象联系起来的模型。在我们的设置中，从网络上向他人学习的过程受确认偏见的影响，即忽略相反的证据并将其解释为与自己的信念一致的趋势。当代理商对自己的注意力足够关注时，确认偏见会导致任何对称网络中的学习速度较慢，并且会增加社会的两极分化。我们确定了与确认偏差更具影响力的一部分药物。社会最佳的网络结构急剧取决于社会规划师可用的信息。当她无法观察到代理人的信念时，最佳网络是对称的，顶点传播的，并且没有自动浮动。我们探讨了这些结果对选举成果和媒体市场的影响。确认偏见增加了冲击选举的可能性，它推动了边缘媒体采取更加极端的意识形态。
In recent years online social networks have become increasingly prominent in political campaigns and, concurrently, several countries have experienced shock election outcomes. This paper proposes a model that links these two phenomena. In our set-up, the process of learning from others on a network is influenced by confirmation bias, i.e. the tendency to ignore contrary evidence and interpret it as consistent with one's own belief. When agents pay enough attention to themselves, confirmation bias leads to slower learning in any symmetric network, and it increases polarization in society. We identify a subset of agents that become more/less influential with confirmation bias. The socially optimal network structure depends critically on the information available to the social planner. When she cannot observe agents' beliefs, the optimal network is symmetric, vertex-transitive and has no self-loops. We explore the implications of these results for electoral outcomes and media markets. Confirmation bias increases the likelihood of shock elections, and it pushes fringe media to take a more extreme ideology.
