社会稳定和扩展的社会平衡-量化社交网络中不活跃链接的作用
Social Stability and Extended Social Balance - Quantifying the Role of Inactive Links in Social Networks
摘要：
社会网络理论中的结构平衡从具有活跃关系（友好或敌对）的签名网络开始，在四种不同类型的三元关系之间建立层次结构。缺少活动链接也会提供有关网络的信息。为了利用结构平衡所揭示的信息，我们引入了不活跃的关系，它解释了两个代理之间的中性和不存在的联系。这种添加导致十种类型的三和弦，其优点是可以对完整网络进行网络分析。对于每种三元关系，我们分配一个能量，这是其平均占用概率的度量。有限的温度解释了三元关系形成中的一种持续的无序形式。我们提出了一个具有三个相互作用项和一个化学势（捕获边缘激活的成本）的哈密顿量作为三元能级的基本模型。我们的模型适合于政治网络的实证分析，并允许发现生成机制。它是在一个扩展的数据集上进行测试的两类联盟之间的排名在一个大型多人在线游戏（MMOG）和现实世界的数据在冷战时期的国家之间的关系。我们发现，在政治网络中的节点之间的三元关系的紧急性质。例如，我们观察到十个三元能级之间跨越时间和网络的持久层次结构。此外，分析揭示了提取的模型参数的一致性和网络的全局属性的派生组合的通用数据崩溃。我们说明，该模型具有预测能力的不同三元态之间的转移概率。
英文摘要：
Structural balance in social network theory starts from signed networks with active relationships (friendly or hostile) to establish a hierarchy between four different types of triadic relationships. The lack of an active link also provides information about the network. To exploit the information that remains uncovered by structural balance, we introduce the inactive relationship that accounts for both neutral and nonexistent ties between two agents. This addition results in ten types of triads, with the advantage that the network analysis can be done with complete networks. To each type of triadic relationship, we assign an energy that is a measure for its average occupation probability. Finite temperatures account for a persistent form of disorder in the formation of the triadic relationships. We propose a Hamiltonian with three interaction terms and a chemical potential (capturing the cost of edge activation) as an underlying model for the triadic energy levels. Our model is suitable for empirical analysis of political networks and allows to uncover generative mechanisms. It is tested on an extended data set for the standings between two classes of alliances in a massively multi-player on-line game (MMOG) and on real-world data for the relationships between countries during the Cold War era. We find emergent properties in the triadic relationships between the nodes in a political network. For example, we observe a persistent hierarchy between the ten triadic energy levels across time and networks. In addition, the analysis reveals consistency in the extracted model parameters and a universal data collapse of a derived combination of global properties of the networks. We illustrate that the model has predictive power for the transition probabilities between the different triadic states.
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