论文标题
对媒体的偏见进行动力：在政治盟友和对手网络中间歇性地改变思想
Vacillating about media bias: changing one's mind intermittently within a network of political allies and opponents
论文作者
论文摘要
意见动力模拟揭示的长期行为的一种形式是间歇性，在这种情况下，稳定，恒定信念和动荡，动荡的信念的时代之间的单个循环，例如在推断媒体组织的政治偏见时。我们通过建立一个理想化的贝叶斯学习者网络来探索这种现象，他们从投掷硬币和政治盟友和对手的同伴压力中推断出硬币的偏见。数值模拟表明，三种类型的网络结构导致了三种不同类型的间歇性，这是由代理人``锁定''对手以特定方式确定信念引起的。在这三种类型的间歇性上，学习者维持稳定或动荡的信念的概率密度功能（学习者都维持稳定或动荡的信念）。因此，至少在原则上，人们可以观察学习者的住所时间来推断潜在的网络结构。
One form of long-term behavior revealed by opinion dynamics simulations is intermittency, where an individual cycles between eras of stable, constant beliefs and turbulent, fluctuating beliefs, for example when inferring the political bias of a media organization. We explore this phenomenon by building an idealized network of Bayesian learners, who infer the bias of a coin from observations of coin tosses and peer pressure from political allies and opponents. Numerical simulations reveal that three types of network structure lead to three different types of intermittency, which are caused by agents ``locking out'' opponents from sure beliefs in specific ways. The probability density functions of the dwell times, over which the learners sustain stable or turbulent beliefs, differ across the three types of intermittency. Hence, one can observe the dwell times of a learner to infer the underlying network structure, at least in principle.
