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Conference Paper: Topological analysis of longitudinal networks

TitleTopological analysis of longitudinal networks
Authors
Issue Date2013
PublisherIEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000730
Citation
The 46th Annual Hawaii International Conference on System Sciences (HICSS 2013), Wailea, Maui, HI., 7-10 January 2013. In Annual Hawaii International Conference on System Sciences Proceedings, 2013 How to Cite?
AbstractLongitudinal networks evolve over time through the addition or deletion of nodes and edges. A longitudinal network can be viewed as a single static network that aggregates all edges observed over some time period (i.e., structure of network is fixed), or as a series of static networks observed in different point of time over the entire network observation period (i.e., structure of network is changing over time). By following a topological approach (i.e., static topology and dynamic topology), this paper first proposes a framework to analyze longitudinal networks. In static topology, SNA methods are applied to the aggregated network of entire observation period. Smaller segments of network data (i.e., short-interval network) that are accumulated in less time compared to the entire network observation period are used in dynamic topology for analysis purpose. Based on this framework, this study then conducts a topological analysis of email communication networks of an organization during its different operational conditions to explore changes in the behavior of actor-level dynamics. © 2012 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/194382
ISSN

 

DC FieldValueLanguage
dc.contributor.authorUddin, S-
dc.contributor.authorPiraveenan, M-
dc.contributor.authorChung, KKS-
dc.contributor.authorHossain, L-
dc.date.accessioned2014-01-30T03:32:31Z-
dc.date.available2014-01-30T03:32:31Z-
dc.date.issued2013-
dc.identifier.citationThe 46th Annual Hawaii International Conference on System Sciences (HICSS 2013), Wailea, Maui, HI., 7-10 January 2013. In Annual Hawaii International Conference on System Sciences Proceedings, 2013-
dc.identifier.issn1530-1605-
dc.identifier.urihttp://hdl.handle.net/10722/194382-
dc.description.abstractLongitudinal networks evolve over time through the addition or deletion of nodes and edges. A longitudinal network can be viewed as a single static network that aggregates all edges observed over some time period (i.e., structure of network is fixed), or as a series of static networks observed in different point of time over the entire network observation period (i.e., structure of network is changing over time). By following a topological approach (i.e., static topology and dynamic topology), this paper first proposes a framework to analyze longitudinal networks. In static topology, SNA methods are applied to the aggregated network of entire observation period. Smaller segments of network data (i.e., short-interval network) that are accumulated in less time compared to the entire network observation period are used in dynamic topology for analysis purpose. Based on this framework, this study then conducts a topological analysis of email communication networks of an organization during its different operational conditions to explore changes in the behavior of actor-level dynamics. © 2012 IEEE.-
dc.languageeng-
dc.publisherIEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000730-
dc.relation.ispartofAnnual Hawaii International Conference on System Sciences Proceedings-
dc.rightsAnnual Hawaii International Conference on System Sciences Proceedings. Copyright © IEEE Computer Society.-
dc.rights©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleTopological analysis of longitudinal networks-
dc.typeConference_Paper-
dc.identifier.emailHossain, L: lhossain@hku.hk-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/HICSS.2013.556-
dc.identifier.scopuseid_2-s2.0-84875514622-
dc.identifier.hkuros243357-
dc.identifier.spage3931-
dc.identifier.epage3940-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 150518-

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