论文标题
不确定信息引起的社会传染
Social contagion induced by uncertain information
论文作者
论文摘要
信息和个人活动通常通过社会关系网络在全球范围内传播。尽管在阈值模型的框架内已经对社会传染现象进行了广泛的研究，但通常在现实中可能会违反的假设是很常见的：每个人都能在没有错误的情况下观察邻居的状态。在这里，我们在不确定性下在原本标准的阈值模型中分析了全球级联反应的动态。每个人都使用统计推断来估计确定是否活跃的活动邻居数量的概率分布，这给出了概率阈值规则。与确定性阈值模型不同，扩散过程通常是非单调的，因为在新信号到达时，可以更新邻居状态的分布。我们发现，社会传染可能是一个自我实现的事件，因为误解可能会引发在确定性永远不会发生级联的地区的级联。
Information and individual activities often spread globally through the network of social ties. While social contagion phenomena have been extensively studied within the framework of threshold models, it is common to make an assumption that may be violated in reality: each individual is able to observe the neighbors' states without error. Here, we analyze the dynamics of global cascades under uncertainty in an otherwise standard threshold model. Each individual uses statistical inference to estimate the probability distribution of the number of active neighbors when deciding whether to be active, which gives a probabilistic threshold rule. Unlike the deterministic threshold model, the spreading process is generally non-monotonic as the inferred distribution of neighbors' states may be updated as a new signal arrives. We find that social contagion may arise as a self-fulfilling event in that misperception may trigger a cascade in regions where cascades would never occur under certainty.
