Detection of Temporal Communities in Mobile Social Networks

被引：0

作者：

Ruan, Mengni ^{[1
]}

Zhou, Huan ^{[1
]}

Li, Dawei ^{[2
]}

Liu, Xuxun ^{[3
]}

Deng, Qingyong ^{[4
]}

机构：

[1] China Three Gorges Univ, Coll Comp & Informat Technol, Yichang, Peoples R China

[2] Montclair State Univ, Dept Comp Sci, Montclair, NJ 07043 USA

[3] South China Univ Technol, Coll Elect & Informat Engn, Guangzhou, Peoples R China

[4] Xiangtan Univ, Coll Informat Engn, Xiangtan 411105, Peoples R China

来源：

IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS) | 2020年

基金：

中国国家自然科学基金;

关键词：

Mobile Social Networks; Temporal Closeness; Temporal Community Detection; Network Model; Community Similarity; CENTRALITY;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In recent years, community detection in Mobile Social Networks (MSNs) has attracted a lot of attentions from both academia and industry areas. The existing methods of community detection usually focus on static networks. However, MSNs in essence are dynamically intermittently connected networks with a time-varying topology. Therefore, this paper proposes a novel temporal community detection method based on nodes' temporal closeness. In order to evaluate the performance of the proposed method and study the evolution law of the temporal community, we conduct extensive simulations using two real mobility traces, the MIT Reality trace and the Infocom 06 trace. The results show that many temporal communities share similar members and appear at different times. Furthermore, we find the periodic appearance of temporal community.

引用

页码：1021 / 1026

页数：6

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