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Conference Paper: Temporal behavior of social network users in information diffusion

TitleTemporal behavior of social network users in information diffusion
Authors
KeywordsInformation Diffusion
User Temporal Behavior
Data mining
Online social network
Issue Date2014
PublisherIEEE Computer Society.
Citation
The 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Workshops (WI-IAT 2014), Warsaw, Poland, 11-14 August 2014. In Conference Proceedings, 2014, v. 2, p. 150-157 How to Cite?
AbstractThe rapid development of online social networks (OSN) renders them a powerful tool for information diffusion. Understanding the temporal behavior of OSN users is critical in studying the diffusion process. While there is much work on building various diffusion models to characterize the information propagation process, the diversity of OSN users' behavior patterns is seldom addressed in these models. However, as revealed by previous measurement studies as well as our empirical observations, OSN users' temporal behaviors are quite different. In this paper, we investigate users' temporal behaviors based on collected traces from a popular OSN in China, covering the diffusion actions of around 2.8 million users for more than 3 years. In particular, distinct from existing studies which mine users' temporal behaviors, we focus on diffusion times and propagation latencies of social links. After clustering the OSN users into two groups with our proposed temporal features, we observe some interesting phenomena, like 'Birds of a feather flock together,' and specifically find that users from different groups behave heterogeneously. Motivated by this observation, we propose a continuous time diffusion model by incorporating users' heterogeneous temporal diffusion patterns. Comparison of simulation results between our model and a homogeneous model demonstrate the necessity of applying our proposed model for more realistic diffusion descriptions. © 2014 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/217396
ISBN

 

DC FieldValueLanguage
dc.contributor.authorNiu, G-
dc.contributor.authorLong, Y-
dc.contributor.authorLi, VOK-
dc.date.accessioned2015-09-18T05:58:22Z-
dc.date.available2015-09-18T05:58:22Z-
dc.date.issued2014-
dc.identifier.citationThe 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Workshops (WI-IAT 2014), Warsaw, Poland, 11-14 August 2014. In Conference Proceedings, 2014, v. 2, p. 150-157-
dc.identifier.isbn978-147994143-8-
dc.identifier.urihttp://hdl.handle.net/10722/217396-
dc.description.abstractThe rapid development of online social networks (OSN) renders them a powerful tool for information diffusion. Understanding the temporal behavior of OSN users is critical in studying the diffusion process. While there is much work on building various diffusion models to characterize the information propagation process, the diversity of OSN users' behavior patterns is seldom addressed in these models. However, as revealed by previous measurement studies as well as our empirical observations, OSN users' temporal behaviors are quite different. In this paper, we investigate users' temporal behaviors based on collected traces from a popular OSN in China, covering the diffusion actions of around 2.8 million users for more than 3 years. In particular, distinct from existing studies which mine users' temporal behaviors, we focus on diffusion times and propagation latencies of social links. After clustering the OSN users into two groups with our proposed temporal features, we observe some interesting phenomena, like 'Birds of a feather flock together,' and specifically find that users from different groups behave heterogeneously. Motivated by this observation, we propose a continuous time diffusion model by incorporating users' heterogeneous temporal diffusion patterns. Comparison of simulation results between our model and a homogeneous model demonstrate the necessity of applying our proposed model for more realistic diffusion descriptions. © 2014 IEEE.-
dc.languageeng-
dc.publisherIEEE Computer Society.-
dc.relation.ispartof2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) Proceedings-
dc.rights2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) Proceedings. Copyright © IEEE.-
dc.rights©2014 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.subjectInformation Diffusion-
dc.subjectUser Temporal Behavior-
dc.subjectData mining-
dc.subjectOnline social network-
dc.titleTemporal behavior of social network users in information diffusion-
dc.typeConference_Paper-
dc.identifier.emailNiu, G: gilniu@eee.hku.hk-
dc.identifier.emailLong, Y: yilong@eee.hku.hk-
dc.identifier.emailLi, VOK: vli@eee.hku.hk-
dc.identifier.authorityLi, VOK=rp00150-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1109/WI-IAT.2014.92-
dc.identifier.scopuseid_2-s2.0-84912565469-
dc.identifier.hkuros254360-
dc.identifier.volume2-
dc.identifier.spage150-
dc.identifier.epage157-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 151103-

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