Community detection in social networks based on information propagation and user engagement

被引:4
作者
Nian, Fuzhong [1 ]
Luo, Li [1 ]
Yu, Xuelong [1 ]
Guo, Xin [1 ]
机构
[1] Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Peoples R China
来源
INTERNATIONAL JOURNAL OF MODERN PHYSICS B | 2021年 / 35卷 / 08期
基金
中国国家自然科学基金;
关键词
Social networks; user engagement; information propagation; community detection; MODULARITY;
D O I
10.1142/S0217979221501198
中图分类号
O59 [应用物理学];
学科分类号
摘要
The iterative propagation of information between nodes will strengthen the connection strength between nodes, and the network can evolve into different groups according to difference edge strength. Based on this observation, we present the user engagement to quantify the influences of users different propagation modes to network propagation, and construct weight network to simulate real social network, and proposed the community detection method in social networks based on information propagation and user engagement. Our method can produce different scale communities and overlapping community. We also applied our method to real-world social networks. The experiment proved that the network spread and the community division interact with each other. The community structure is significantly different in the network propagation of different scales.
引用
收藏
页数:14
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