英文标题：
《Community detection in temporal multilayer networks, with an application
  to correlation networks》
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作者：
Marya Bazzi, Mason A. Porter, Stacy Williams, Mark McDonald, Daniel J.
  Fenn, and Sam D. Howison
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最新提交年份：
2017
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英文摘要：
  Networks are a convenient way to represent complex systems of interacting entities. Many networks contain \"communities\" of nodes that are more densely connected to each other than to nodes in the rest of the network. In this paper, we investigate the detection of communities in temporal networks represented as multilayer networks. As a focal example, we study time-dependent financial-asset correlation networks. We first argue that the use of the \"modularity\" quality function---which is defined by comparing edge weights in an observed network to expected edge weights in a \"null network\"---is application-dependent. We differentiate between \"null networks\" and \"null models\" in our discussion of modularity maximization, and we highlight that the same null network can correspond to different null models. We then investigate a multilayer modularity-maximization problem to identify communities in temporal networks. Our multilayer analysis only depends on the form of the maximization problem and not on the specific quality function that one chooses. We introduce a diagnostic to measure \\emph{persistence} of community structure in a multilayer network partition. We prove several results that describe how the multilayer maximization problem measures a trade-off between static community structure within layers and larger values of persistence across layers. We also discuss some computational issues that the popular \"Louvain\" heuristic faces with temporal multilayer networks and suggest ways to mitigate them.
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中文摘要：
网络是一种表示相互作用实体的复杂系统的便捷方式。许多网络包含节点的“社区”，这些节点之间的连接比其他网络中的节点更紧密。在本文中，我们研究了在表示为多层网络的时态网络中的社区检测。作为一个重点例子，我们研究了时间相关的金融资产关联网络。首先，我们认为“模块化”质量函数的使用取决于应用程序，该函数是通过比较观察到的网络中的边缘权重与“空网络”中的预期边缘权重来定义的。在模块化最大化的讨论中，我们区分了“零网络”和“零模型”，并强调同一个零网络可以对应不同的零模型。然后，我们研究了一个多层模块化最大化问题，以确定时态网络中的社区。我们的多层分析只取决于最大化问题的形式，而不取决于所选择的具体质量函数。我们将{emph}的多层网络划分引入到诊断}。我们证明了几个结果，这些结果描述了多层最大化问题如何衡量层内静态社区结构和层间更大持久性值之间的权衡。我们还讨论了流行的“Louvain”启发式算法在时间多层网络中面临的一些计算问题，并提出了缓解这些问题的方法。
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分类信息：

一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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一级分类：Computer Science        计算机科学
二级分类：Social and Information Networks        社会和信息网络
分类描述：Covers the design, analysis, and modeling of social and information networks, including their applications for on-line information access, communication, and interaction, and their roles as datasets in the exploration of questions in these and other domains, including connections to the social and biological sciences. Analysis and modeling of such networks includes topics in ACM Subject classes F.2, G.2, G.3, H.2, and I.2; applications in computing include topics in H.3, H.4, and H.5; and applications at the interface of computing and other disciplines include topics in J.1--J.7. Papers on computer communication systems and network protocols (e.g. TCP/IP) are generally a closer fit to the Networking and Internet Architecture (cs.NI) category.
涵盖社会和信息网络的设计、分析和建模，包括它们在联机信息访问、通信和交互方面的应用，以及它们作为数据集在这些领域和其他领域的问题探索中的作用，包括与社会和生物科学的联系。这类网络的分析和建模包括ACM学科类F.2、G.2、G.3、H.2和I.2的主题；计算应用包括H.3、H.4和H.5中的主题；计算和其他学科接口的应用程序包括J.1-J.7中的主题。关于计算机通信系统和网络协议（例如TCP/IP）的论文通常更适合网络和因特网体系结构（CS.NI）类别。
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一级分类：Physics        物理学
二级分类：Adaptation and Self-Organizing Systems        自适应和自组织系统
分类描述：Adaptation, self-organizing systems, statistical physics, fluctuating systems, stochastic processes, interacting particle systems, machine learning
自适应，自组织系统，统计物理，波动系统，随机过程，相互作用粒子系统，机器学习
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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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