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Conference Paper: Measurement-driven temporal analysis of information diffusion in online social networks

TitleMeasurement-driven temporal analysis of information diffusion in online social networks
Authors
KeywordsActivation time
Diffusion
Measurement
Social network
Temporal
Issue Date2012
PublisherIEEE. The Journal's web site is located at http://www.ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000308
Citation
The 2012 IEEE Global Communications Conference (GLOBECOM), Anaheim, CA., 3-7 December 2012. In Globecom. IEEE Conference and Exhibition, 2012, p. 2060-2065 How to Cite?
AbstractThe rapid development of online social networks (OSN) renders them a popular mechanism for information diffusion. Studying the temporal characteristics is critical in understanding the diffusion process. However, due to the lack of well-defined propagation data, hardly any study addresses the temporal feature of information diffusion in OSN. In this paper, we present a measurement study on information diffusion in the Renren social network. We investigate the latency of information propagation along social links and define the 'activation time' for an OSN user, and find that the activation time follows the lognormal distribution. Based on this, we develop two new information diffusion models incorporating asynchronous activation times. Application of the models in the influence maximization problem shows that they capture the temporal diffusion behavior very well. This leads to fundamental ramifications to many related OSN applications. © 2012 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/191615
ISBN
ISSN

 

DC FieldValueLanguage
dc.contributor.authorNiu, Gen_US
dc.contributor.authorLi, VOKen_US
dc.contributor.authorLong, Yen_US
dc.contributor.authorXu, Ken_US
dc.date.accessioned2013-10-15T07:14:40Z-
dc.date.available2013-10-15T07:14:40Z-
dc.date.issued2012en_US
dc.identifier.citationThe 2012 IEEE Global Communications Conference (GLOBECOM), Anaheim, CA., 3-7 December 2012. In Globecom. IEEE Conference and Exhibition, 2012, p. 2060-2065en_US
dc.identifier.isbn978-1-4673-0921-9-
dc.identifier.issn1930-529X-
dc.identifier.urihttp://hdl.handle.net/10722/191615-
dc.description.abstractThe rapid development of online social networks (OSN) renders them a popular mechanism for information diffusion. Studying the temporal characteristics is critical in understanding the diffusion process. However, due to the lack of well-defined propagation data, hardly any study addresses the temporal feature of information diffusion in OSN. In this paper, we present a measurement study on information diffusion in the Renren social network. We investigate the latency of information propagation along social links and define the 'activation time' for an OSN user, and find that the activation time follows the lognormal distribution. Based on this, we develop two new information diffusion models incorporating asynchronous activation times. Application of the models in the influence maximization problem shows that they capture the temporal diffusion behavior very well. This leads to fundamental ramifications to many related OSN applications. © 2012 IEEE.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://www.ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000308-
dc.relation.ispartofGlobecom. IEEE Conference and Exhibitionen_US
dc.rightsGlobecom. IEEE Conference and Exhibition. Copyright © IEEE.-
dc.rights©2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectActivation time-
dc.subjectDiffusion-
dc.subjectMeasurement-
dc.subjectSocial network-
dc.subjectTemporal-
dc.titleMeasurement-driven temporal analysis of information diffusion in online social networksen_US
dc.typeConference_Paperen_US
dc.identifier.emailNiu, G: glniu@eee.hku.hken_US
dc.identifier.emailLi, VOK: vli@eee.hku.hk-
dc.identifier.emailLong, Y: yilong@eee.hkuhk-
dc.identifier.emailXu, K: xukuang@eee.hku.hk-
dc.identifier.authorityLi, VOK=rp00150en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/GLOCOM.2012.6503419-
dc.identifier.scopuseid_2-s2.0-84877645626-
dc.identifier.hkuros225557en_US
dc.identifier.spage2060-
dc.identifier.epage2065-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 131106-

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