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Conference Paper: Investigating attachment behavior of nodes during evolution of a complex social network: A case of a scientific collaboration network

TitleInvestigating attachment behavior of nodes during evolution of a complex social network: A case of a scientific collaboration network
Authors
Issue Date2011
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011, v. 6882 LNAI n. PART 2, p. 256-264 How to Cite?
AbstractComplex networks (systems) as a phenomenon can be observed by a wide range of networks in nature and society. There is a growing interest to study complex networks from the evolutionary and behavior perspective. Studies on evolving dynamical networks have been resulted in a class of models to explain their evolving dynamic behavior that indicate a new node attaches preferentially to some old nodes in the network based on their number of links. In this study, we aim to explore if there are any other characteristics of the old nodes which affect on the preferential attachment of new nodes. We explore the evolution ofa co-authorship network over time and find that while the association between number of new attached nodes to an existing node and all its main centrality measures (i.e., degree, closeness and betweenness) is almost positive and significant but betweenness centrality correlation coefficient is always higher and increasing as network evolved over time. Identifying the attachment behavior of nodes in complex networks (e.g., traders, disease propagation and emergency management) help policy and decision makers to focus on the nodes (actors) in order to control the resources distribution, information dissemination, disease propagation and so on due to type of the network. © 2011 Springer-Verlag.
Persistent Identifierhttp://hdl.handle.net/10722/194325
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorAbbasi, A-
dc.contributor.authorHossain, L-
dc.date.accessioned2014-01-30T03:32:27Z-
dc.date.available2014-01-30T03:32:27Z-
dc.date.issued2011-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011, v. 6882 LNAI n. PART 2, p. 256-264-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/194325-
dc.description.abstractComplex networks (systems) as a phenomenon can be observed by a wide range of networks in nature and society. There is a growing interest to study complex networks from the evolutionary and behavior perspective. Studies on evolving dynamical networks have been resulted in a class of models to explain their evolving dynamic behavior that indicate a new node attaches preferentially to some old nodes in the network based on their number of links. In this study, we aim to explore if there are any other characteristics of the old nodes which affect on the preferential attachment of new nodes. We explore the evolution ofa co-authorship network over time and find that while the association between number of new attached nodes to an existing node and all its main centrality measures (i.e., degree, closeness and betweenness) is almost positive and significant but betweenness centrality correlation coefficient is always higher and increasing as network evolved over time. Identifying the attachment behavior of nodes in complex networks (e.g., traders, disease propagation and emergency management) help policy and decision makers to focus on the nodes (actors) in order to control the resources distribution, information dissemination, disease propagation and so on due to type of the network. © 2011 Springer-Verlag.-
dc.languageeng-
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.titleInvestigating attachment behavior of nodes during evolution of a complex social network: A case of a scientific collaboration network-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-642-23863-5_26-
dc.identifier.scopuseid_2-s2.0-80053139797-
dc.identifier.volume6882 LNAI-
dc.identifier.issuePART 2-
dc.identifier.spage256-
dc.identifier.epage264-

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