网络拓扑推理与网络社会网络中的确认偏差
On Inference of Network Topology and Confirmation Bias in Cyber-Social Networks
摘要：
本文研究了一个有向网络社会网络的拓扑推理，从主体状态，意见传播动力学模型，明确考虑确认偏差。网络社交网络包括社交层面的一组部分连接的有向代理网络和网络层的一组信息源。刻画了精确推理解存在的充分必要条件。对于前面提到的偏置遵循分段线性模型的情况，提出了一种在可能的情况下精确推断整个网络拓扑以及确认偏置模型参数的方法。对无确认偏倚的特殊情况进行了详细分析。对于确认偏差模型未知的情况，提出了一种基于精确推理方法的网络拓扑近似算法。该算法能够准确地推断出信息源的邻居与非跟随者之间的加权通信。数值仿真结果表明，所提出的方法对不同的场景的有效性。
英文摘要：
This paper studies topology inference, from agent states, of a directed cyber-social network with opinion spreading dynamics model that explicitly takes confirmation bias into account. The cyber-social network comprises a set of partially connected directed network of agents at the social level, and a set of information sources at the cyber layer. The necessary and sufficient conditions for the existence of exact inference solution are characterized. A method for exact inference, when it is possible, of entire network topology as well as confirmation bias model parameters is proposed for the case where the bias mentioned earlier follows a piece-wise linear model. The particular case of no confirmation bias is analyzed in detail. For the setting where the model of confirmation bias is unknown, an algorithm that approximates the network topology, building on the exact inference method, is presented. This algorithm can exactly infer the weighted communication from the neighbors to the non-followers of information sources. Numerical simulations demonstrate the effectiveness of the proposed methods for different scenarios.
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