Social networks are made up of members in society and the social relationships established by the interaction between members. Community structure is an essential attribute of social networks. The question arises that how can we discover the community structure in the network to gain a deep understanding of its underlying structure and mine information from it? In this paper, we introduce a novel community detection algorithm NTCD (Community Detection based on Node Trust). This is a stable community detection algorithm that does not require any parameters settings and has nearly linear time complexity. NTCD determines the community ownership of a node by studying the relationship between the node and its neighbor communities. This relationship is called Node Trust, representing the possibility that the node is in the current community. Node Trust is also a quality function, which is used for community detection by seeking maximum. Experiments on real and synthetic networks show that our algorithm has high accuracy in most data sets and stable community division results. Additionally, through experiments on different types of synthetic networks, we can conclude that our algorithm has good robustness.

中文翻译：

---

节点信任：一种检测社交网络中非重叠社区的有效方法

社交网络是由社会中的成员和成员之间的互动所建立的社会关系组成的。社区结构是社交网络的基本属性。问题来了，我们如何才能发现网络中的社区结构，从而深入了解其底层结构并从中挖掘信息？在本文中，我们介绍了一种新颖的社区检测算法 NTCD（基于节点信任的社区检测）。这是一种稳定的社区检测算法，不需要任何参数设置，时间复杂度接近线性。NTCD 通过研究节点与其相邻社区之间的关系来确定节点的社区所有权。这种关系称为节点信任，代表节点在当前社区中的可能性。节点信任也是一个质量函数，用于寻求最大值的社区检测。在真实网络和合成网络上的实验表明，我们的算法在大多数数据集上都具有较高的准确性和稳定的社区划分结果。此外，通过对不同类型合成网络的实验，我们可以得出结论，我们的算法具有良好的鲁棒性。