...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Bulletin of the American Physical Society >APS -APS March Meeting 2017 - Event - Opinion Dynamics on Networks with Inference of Unobservable States of Others
【24h】

APS -APS March Meeting 2017 - Event - Opinion Dynamics on Networks with Inference of Unobservable States of Others

机译：APS -APS 2017年3月会议-事件-推断其他人无法观察到的状态下的网络舆论动态

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In most opinion formation models which have been proposed, the agents decide their states (i.e. opinions) by referring to the states of others. However, the referred states of others are not necessarily observable and may be inferred. To investigate the effect of an inference of the states of others on opinion dynamics, I propose an extended voter model on networks where observable and referable node sets are different. These sets for a node defined as the nearest to the $m_o$-th neighbors for observable nodes and the nearest to the $m_r$-th neighbors for referable nodes. The state of referable but unobservable node which is the $m$-th neighbor ($m_o< mle m_r$) is inferred by using the observed or inferred states of the ($m-1$)-th neighbors. In the case of $m_o=1$ and $m_r=N$, I show analytically that the linear superposition of the states weighted by ``betweenness pagerank'' is conserved. This conserved quantity coincides with the fixation probability. On the other hand, in the case of $m_o=m_r=1$, the model comes down to the standard voter model on networks and the conserved quantity is a degree-weighted superposition of the states. Thus, the introduction of the inference changes the important opinion spreaders from the high-degree nodes to the high-betweenness pagerank nodes.
机译：在大多数提出的意见形成模型中，代理人通过参考他人的状态来决定他们的状态（即意见）。但是，其他人的引用状态不一定是可观察的，并且可以推断出来。为了研究他人状态推断对意见动态的影响，我提出了在可观察节点集和可参照节点集不同的网络上的扩展选民模型。这些为节点设置，对于可观察节点，将其定义为最靠近第mm个邻居，对于可参考节点，将其定义为最靠近第mmr个邻居。通过使用第（m-1）个邻居的观察或推断状态来推断可参考但不可观察的节点的状态，即第m $个邻居（$ m_o

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号