论文标题
离散代理人信息网络中的社区结构
Community Structures in Information Networks for a Discrete Agent Population
论文作者
论文摘要
社区是社交网络的重要特征。本文的目的是提出一个数学模型，以研究社交网络中的社区结构。为此，我们考虑了社交网络的特定情况，即信息网络。我们假设有一群有兴趣获得内容的代理商。代理商在他们感兴趣的内容类型上有所不同。代理的目标是形成社区，以最大程度地提高其获得和生产内容的效用。我们使用此模型来表征在这种情况下以NASH平衡形成的社区的结构。本文介绍的工作概括了有关连续代理模型的文献，即离散代理人群体模型的情况。我们注意到，离散代理集反映了更准确的现实信息网络，因此需要对社区结构进行更多见解，例如社区内的连接性（图形结构），以及社区内的信息传播。
Communities are an important feature of social networks. The goal of this paper is to propose a mathematical model to study the community structure in social networks. For this, we consider a particular case of a social network, namely information networks. We assume that there is a population of agents who are interested in obtaining content. Agents differ in the type of content they are interested in. The goal of agents is to form communities in order to maximize their utility for obtaining and producing content. We use this model to characterize the structure of communities that emerge as a Nash equilibrium in this setting. The work presented in this paper generalizes results in the literature that were obtained for the case of a continuous agent model, to the case of a discrete agent population model. We note that a discrete agent set reflects more accurately real-life information networks, and are needed in order to get additional insights into the community structure, such as for example the connectivity (graph structure) within in a community, as well as information dissemination within a community.
