False Information and Disagreement in Social Networks
False Information and Disagreement in Social Networks
复制标题
社交网络中的虚假信息和分歧
DOI：
10.2139/ssrn.3074552
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
E. Sadler
中科院分区：
文献类型：
--
作者：
E. Sadler
分歧，包括对事实的分歧，是一种普遍现象，但这与现有的社会学习工作不相容。我提出了一个模型的信息处理有两个关键特征：（一）代理遇到错误的信息，（二）代理不能区分真假命题。我研究了两个家庭的更新规则的公理，发现“愿意学习”公理是不兼容的“非操纵性”公理。我还提供了几个更新规则的公理化特征。在一个简单的社会学习模型中，分歧不仅是可能的，而且是普遍的。我的特点是每个代理人的影响，稳态信念和应用框架来研究回声室和信念操纵。
Disagreement, including on matters of fact, is a pervasive phenomenon, yet this is incompatible with existing work on social learning. I propose a model of information processing with two key features: (i) the agent encounters false information, and (ii) the agent cannot distinguish true propositions from false ones. I study two families of axioms for update rules, finding that ``willingness-to-learn'' axioms are incompatible with ``non-manipulability'' axioms. I also provide an axiomatic characterization of several update rules. In a simple social learning model, disagreement is not just possible, but generic. I characterize the influence of each agent on steady-state beliefs and apply the framework to study echo chambers and belief manipulation.