Evolutionary community structure discovery in dynamic weighted networks

Chonghui Guo, Jiajia Wang and Zhen Zhang

Physica A: Statistical Mechanics and its Applications, 2014, vol. 413, issue C, 565-576

Abstract: Detecting evolutionary community structure in dynamic weighted networks is important for understanding the structure and functions of networks. In this paper, an algorithm which considers the historic community structure of networks is developed to detect evolutionary community structure in dynamic weighted networks. In the proposed algorithm, two measures are proposed to determine whether to add a node to a community and whether to merge two communities to form a new community. The proposed algorithm can automatically discover evolutionary community structure in weighted networks whose number of nodes and communities is changing over time and does not need to determine the number of communities in advance. The algorithm is tested using a synthetic network and two real-word complex networks. Experimental results demonstrate that the proposed algorithm can discover evolutionary community structure in dynamic weighted networks effectively.

Keywords: Dynamic networks; Evolution; Community structure; Weighted networks (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S037843711400569X
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:413:y:2014:i:c:p:565-576

DOI: 10.1016/j.physa.2014.07.004

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().