Maps of Information Flow Reveal Community Structure In Complex Networks
Maps of Information Flow Reveal Community Structure In Complex Networks
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发表时间：
2007-07
影响因子：
10.5
通讯作者：
M. Rosvall;Carl T. Bergstrom
中科院分区：
文献类型：
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作者：
M. Rosvall;Carl T. Bergstrom
为了理解大规模生物和社会系统的多方组织，我们引入了一种新的信息论方法来揭示加权有向网络中的群落结构。该方法通过最优地压缩网络上的信息流的描述来将网络分解成模块。其结果是一张既简化又突出结构及其关系的规则的地图。我们通过绘制一张科学交流地图来说明这一方法，该地图捕捉到了6000多种期刊的引文模式。我们发现了一个多中心的组织，其领域在大小和融入科学网络的程度上都有很大的差异。沿着网络的背面--包括物理、化学、分子生物学和医学--信息双向流动，但这张地图揭示了从应用领域到基础科学的引用方向模式。
To comprehend the multipartite organization of large-scal e biological and social systems, we introduce a new information theoretic approach to reveal community struct ure in weighted and directed networks. The method decomposes a network into modules by optimally compressing a description of information flows on the network. The result is a map that both simplifies and highlights the reg ularities in the structure and their relationships. We illustrate the method by making a map of scientific communica tion as captured in the citation patterns of more than 6000 journals. We discover a multicentric organizatio n with fields that vary dramatically in size and degree of integration into the network of science. Along the backbo ne f the network — including physics, chemistry, molecular biology, and medicine — information flows bidirec tionally, but the map reveals a directional pattern of citation from the applied fields to the basic sciences.