Dynamic Epistemic Logics of Diffusion and Prediction in Social Networks
Dynamic Epistemic Logics of Diffusion and Prediction in Social Networks
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DOI：
10.1007/s11225-018-9804-x
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发表时间：
2018-07
期刊：
影响因子：
0.7
通讯作者：
A. Baltag;Z. Christoff;R. K. Rendsvig;S. Smets
中科院分区：
文献类型：
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作者：
A. Baltag;Z. Christoff;R. K. Rendsvig;S. Smets
我们对阈值模型采取一种合乎逻辑的方法，该模型用于研究观点、新技术、感染或社交网络中的行为的传播。门限模型由通过社会关系连接的代理的网络图和调节扩散过程的门限值组成。当他们的邻居已经采用了一种新的行为/产品/意见的比例达到门槛时，代理人就会采用这种新的行为/产品/意见。在这种扩散策略下，阈值模型向保证不动点动态发展。我们构造了一个最小动态命题逻辑来描述门限动态，并证明了该逻辑是可靠和完备的。然后，我们用认知维度扩展了这个框架，并调查关于较远邻居的行为的信息如何允许代理预测他们较近邻居的行为变化。总体而言，我们的逻辑形式主义捕捉到了社交网络中认知维度和社交维度之间的相互作用。
We take a logical approach to threshold models, used to study the diffusion of opinions, new technologies, infections, or behaviors in social networks. Threshold models consist of a network graph of agents connected by a social relationship and a threshold value which regulates the diffusion process. Agents adopt a new behavior/product/opinion when the proportion of their neighbors who have already adopted it meets the threshold. Under this diffusion policy, threshold models develop dynamically towards a guaranteed fixed point. We construct a minimal dynamic propositional logic to describe the threshold dynamics and show that the logic is sound and complete. We then extend this framework with an epistemic dimension and investigate how information about more distant neighbors’ behavior allows agents to anticipate changes in behavior of their closer neighbors. Overall, our logical formalism captures the interplay between the epistemic and social dimensions in social networks.