Research on Statistical Feature of Online Social Networks Based on Complex Network Theory

Xin Jin, Jianyu Li
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引用次数: 2

Abstract

At present, the study of complex networks include the geometric nature of the network, the formation mechanism of the network, the statistical law of the network evolution, the model property on the network, the structure stability of the network, and other issues like network evolution and dynamic mechanics, etc. There into, in the field of natural science, the basic measuring of the network research includes degree and its distribution characteristic, relevancy of degree, clustering and its distribution characteristics, shortest path and its distribution characteristics, sparsity and its distribution characteristics, and size distribution of connected groups. In order to depict the complex network topology, scholars have proposed many methods to describe the statistical parameter and measurement for complex network features. The OSN will be briefly analyzed below by using these important concepts. At last, the research significance of the online social network, the value of theory, potential applications and research direction in future have been summed up.
基于复杂网络理论的在线社会网络统计特征研究
目前,对复杂网络的研究包括网络的几何性质、网络的形成机制、网络演化的统计规律、网络的模型性质、网络的结构稳定性以及网络演化和动态力学等问题。其中,在自然科学领域中,网络研究的基本度量包括程度及其分布特征、关联度、聚类及其分布特征、最短路径及其分布特征、稀疏性及其分布特征、连接群的大小分布等。为了描述复杂的网络拓扑结构,学者们提出了许多方法来描述复杂网络特征的统计参数和测量。下面将使用这些重要概念对OSN进行简要分析。最后,总结了在线社交网络的研究意义、理论价值、潜在应用以及未来的研究方向。
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