Opinion Dynamics and Learning in Social Networks
Opinion Dynamics and Learning in Social Networks
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DOI：
10.1007/s13235-010-0004-1
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发表时间：
2011-03-01
影响因子：
1.5
通讯作者：
Ozdaglar, Asuman
中科院分区：
文献类型：
--
作者：
Acemoglu, Daron;Ozdaglar, Asuman
我们提供了一个概述，最近的研究信念和意见动态社交网络。我们讨论了社会学习的贝叶斯和非贝叶斯模型，并重点讨论了学习形式的含义（例如：例如，在一个实施例中，贝叶斯与非贝叶斯），信息来源（e。例如，在一个实施例中，观察与交流），以及个体所处的社交网络的结构，这三个关键问题是：（1）社会学习是否会导致共识，即，这些问题包括：（1）不同观点的个体之间的一致性;（2）社会学习是否会有效地聚集分散的信息，从而剔除不正确的信念;（3）媒体来源，着名的代理人，政治家和国家是否能够操纵信念并在社会中传播错误信息。
We provide an overview of recent research on belief and opinion dynamics in social networks. We discuss both Bayesian and non-Bayesian models of social learning and focus on the implications of the form of learning (e. g., Bayesian vs. non-Bayesian), the sources of information (e. g., observation vs. communication), and the structure of social networks in which individuals are situated on three key questions: (1) whether social learning will lead to consensus, i.e., to agreement among individuals starting with different views; (2) whether social learning will effectively aggregate dispersed information and thus weed out incorrect beliefs; (3) whether media sources, prominent agents, politicians and the state will be able to manipulate beliefs and spread misinformation in a society.