Dong Jian, Chen Bin, Zhang Pengfei, Ai Chuan, Zhang Fang, Guo Danhuai, Qiu Xiaogang
College of System Engineering, National University of Defense Technology, Changsha 410073, China.
Computer Network Information Center, Chinese Academy of Sciences, 4th South Fourth Road Zhongguancun, Beijing 100190, China.
Entropy (Basel). 2019 Apr 24;21(4):434. doi: 10.3390/e21040434.
The development of online social networking services provides a rich source of data of social networks including geospatial information. More and more research has shown that geographical space is an important factor in the interactions of users in social networks. In this paper, we construct the spatial interaction network from the city level, which is called the city interaction network, and study the evolution mechanism of the city interaction network formed in the process of information dissemination in social networks. A network evolution model for interactions among cities is established. The evolution model consists of two core processes: the edge arrival and the preferential attachment of the edge. The edge arrival model arranges the arrival time of each edge; the model of preferential attachment of the edge determines the source node and the target node of each arriving edge. Six preferential attachment models (Random-Random, Random-Degree, Degree-Random, Geographical distance, Degree-Degree, Degree-Degree-Geographical distance) are built, and the maximum likelihood approach is used to do the comparison. We find that the degree of the node and the geographic distance of the edge are the key factors affecting the evolution of the city interaction network. Finally, the evolution experiments using the optimal model DDG are conducted, and the experiment results are compared with the real city interaction network extracted from the information dissemination data of the WeChat web page. The results indicate that the model can not only capture the attributes of the real city interaction network, but also reflect the actual characteristics of the interactions among cities.
在线社交网络服务的发展提供了包括地理空间信息在内的丰富社交网络数据来源。越来越多的研究表明,地理空间是社交网络中用户互动的一个重要因素。在本文中,我们从城市层面构建空间互动网络,即城市互动网络,并研究社交网络信息传播过程中形成的城市互动网络的演化机制。建立了一个城市间互动的网络演化模型。该演化模型由两个核心过程组成:边的到达和边的优先连接。边到达模型安排每条边的到达时间;边优先连接模型确定每条到达边的源节点和目标节点。构建了六个优先连接模型(随机-随机、随机-度、度-随机、地理距离、度-度、度-度-地理距离),并使用最大似然法进行比较。我们发现节点的度和边的地理距离是影响城市互动网络演化的关键因素。最后,使用最优模型DDG进行演化实验,并将实验结果与从微信网页信息传播数据中提取的真实城市互动网络进行比较。结果表明,该模型不仅能够捕捉真实城市互动网络的属性,还能反映城市间互动的实际特征。