Community Vitality in Dynamic Temporal Networks
Joint Authors
Min, Li
Lansheng, Han
Park, Jong Hyuk
Deqing, Zou
Shuyan, Qu
Cai, Fu
Source
International Journal of Distributed Sensor Networks
Issue
Vol. 2013, Issue - (31 Dec. 2013), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-26
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Telecommunications Engineering
Information Technology and Computer Science
Abstract EN
Current researches on temporal networks mainly tend to detect community structure.
A number of community detection algorithms can obtain community structure on each time slice or each period of time but rarely present the evolution of community structure.
Some papers discussed the process of community structure evolution but lacked quantifying the evolution.
In this paper, we put forward the concept of Community Vitality (CV), which shows a community's life intensity on a time slice.
In the process of computing CV, the “dead communities” can also be distinguished.
Moreover, CV cannot only be used to quantify the life intensity of a community but also be used to describe the process of community evolution over time.
More specifically, the change of community’s structure will be found if CVs for different time slices of a community were compared, while the community with big value of CV can be selected if CVs for different communities were compared.
Furthermore, community vitality change rate (CVCR) is proposed for revealing communities' structure change.
The results of our experiments show that community vitality is a novel and effective way to understand or model the community evolution.
American Psychological Association (APA)
Cai, Fu& Min, Li& Deqing, Zou& Shuyan, Qu& Lansheng, Han& Park, Jong Hyuk. 2013. Community Vitality in Dynamic Temporal Networks. International Journal of Distributed Sensor Networks،Vol. 2013, no. -, pp.1-10.
https://search.emarefa.net/detail/BIM-460015
Modern Language Association (MLA)
Cai, Fu…[et al.]. Community Vitality in Dynamic Temporal Networks. International Journal of Distributed Sensor Networks Vol. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-460015
American Medical Association (AMA)
Cai, Fu& Min, Li& Deqing, Zou& Shuyan, Qu& Lansheng, Han& Park, Jong Hyuk. Community Vitality in Dynamic Temporal Networks. International Journal of Distributed Sensor Networks. 2013. Vol. 2013, no. -, pp.1-10.
https://search.emarefa.net/detail/BIM-460015
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-460015