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International Conference on Business Information Systems

BIS 2019: Business Information Systems pp 62–73Cite as

Influential Nodes Detection in Dynamic Social Networks

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 354))

Abstract

The influence maximization problem aims to identify influential nodes allowing to reach the viral marketing objectives on social networks. Previous researches are mainly concerned with the static social network analysis and the development of algorithms in this context. However, when network changes, those algorithms must be updated. In this paper, we offer a new interesting approach to study the influential nodes detection problem in changing social networks. This approach can be considered to be an extension of a previous static algorithm SND (Semantic and structural influential Nodes Detection). Experimental results prove the effectiveness of SNDUpdate to detect influential nodes in dynamic social networks.

MARS—Modeling of Automated Reasoning Systems.

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Author information

Authors and Affiliations

  1. Laboratoire MARS LR17ES05, ISITCom, Université de Sousse, 4011, Sousse, Tunisie

    Nesrine Hafiene, Wafa Karoui & Lotfi Ben Romdhane

  2. ISITCom, Université de Sousse, 4011, Sousse, Tunisie

    Nesrine Hafiene & Lotfi Ben Romdhane

  3. ISI, Université de Tunis El Manar, 2080, Tunis, Tunisie

    Wafa Karoui

Authors
  1. Nesrine Hafiene
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  2. Wafa Karoui
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  3. Lotfi Ben Romdhane
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Corresponding author

Correspondence to Nesrine Hafiene .

Editor information

Editors and Affiliations

  1. Poznań University of Economics and Business, Poznań, Poland

    Witold Abramowicz

  2. ETSI Informática, University of Seville, Seville, Spain

    Rafael Corchuelo

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Hafiene, N., Karoui, W., Ben Romdhane, L. (2019). Influential Nodes Detection in Dynamic Social Networks. In: Abramowicz, W., Corchuelo, R. (eds) Business Information Systems. BIS 2019. Lecture Notes in Business Information Processing, vol 354. Springer, Cham. https://doi.org/10.1007/978-3-030-20482-2_6

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  • DOI: https://doi.org/10.1007/978-3-030-20482-2_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20481-5

  • Online ISBN: 978-3-030-20482-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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