Balance in signed networks
Balance in signed networks
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DOI：
10.1103/physreve.99.012320
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发表时间：
2019-01-22
影响因子：
2.4
通讯作者：
Newman, M. E. J.
中科院分区：
文献类型：
--
作者：
Kirkley, Alec;Cantwell, George T.;Newman, M. E. J.
我们考虑签名网络，其中的连接或边缘可以是积极的（友谊、信任、联盟）或消极的（不喜欢、不信任、冲突）。早期的图论文献认为，这样的网络应该表现出“结构平衡”，这意味着某些正边和负边的配置是受欢迎的，而另一些则不受欢迎。在这里，我们基于弱平衡和强平衡的既定概念提出了签名网络中的两种平衡度量，并将它们在一系列任务中的表现相互比较，并与之前提出的度量进行比较。特别是，我们询问与适当的零模型相比，这些度量是否显着平衡了现实世界的签名网络，并发现确实如此，通过所有研究的度量。我们还通过最大化平衡来测试我们在已知网络中预测未知信号的能力。在一系列的交叉验证测试中，我们发现我们的方法能够比偶然更好地预测迹象。
We consider signed networks in which connections or edges can be either positive (friendship, trust, alliance) or negative (dislike, distrust, conflict). Early literature in graph theory theorized that such networks should display "structural balance," meaning that certain configurations of positive and negative edges are favored and others are disfavored. Here we propose two measures of balance in signed networks based on the established notions of weak and strong balance, and we compare their performance on a range of tasks with each other and with previously proposed measures. In particular, we ask whether real-world signed networks are significantly balanced by these measures compared to an appropriate null model, finding that indeed they are, by all the measures studied. We also test our ability to predict unknown signs in otherwise known networks by maximizing balance. In a series of cross-validation tests we find that our measures are able to predict signs substantially better than chance.