论文标题
骨干：提取网络骨干的R软件包
backbone: An R package to extract network backbones
论文作者
论文摘要
网络对于表示广泛域中的现象很有用。尽管它们代表复杂性的能力可能是一种美德，但有时专注于仅包含最重要边缘的简化网络是有用的：骨干。本文介绍并演示了R的“骨干”软件包，该软件包实现了从加权网络，加权两部分投影和未加权网络中提取骨干的方法。对于每种类型的网络，首先为小型玩具示例提供了完全可复制的代码，然后使用交通，政治和社交网络进行完整的经验示例。该论文还证明了骨干提取中出现的几个统计推断问题的含义。它结束时，使用“骨干”软件包简要审查了主干提取的现有应用，以及用于网络骨干萃取的未来方向。
Networks are useful for representing phenomena in a broad range of domains. Although their ability to represent complexity can be a virtue, it is sometimes useful to focus on a simplified network that contains only the most important edges: the backbone. This paper introduces and demonstrates the `backbone' package for R, which implements methods for extracting the backbone from weighted networks, weighted bipartite projections, and unweighted networks. For each type of network, fully replicable code is presented first for small toy examples, then for complete empirical examples using transportation, political, and social networks. The paper also demonstrates the implications of several issues of statistical inference that arise in backbone extraction. It concludes by briefly reviewing existing applications of backbone extraction using the `backbone' package, and future directions for research on network backbone extraction.
