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OMT: An Operate-Based Approach for Modelling Multi-topic Influence Diffusion in Online Social Networks

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Web Information Systems Engineering – WISE 2021 (WISE 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13080))

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Abstract

Influence diffusion modelling in online social networks has been widely studied and applied in public opinion management, viral marketing, and rumour detection. Most existing studies focus on the network topology and the complex user characteristics while ignoring the diverse topic features of the information, especially the cross-impact of multiple topics on the information propagation. In this paper, we propose the Operator-based Multi-Topic (OMT) model by considering user topic interest, topic penetration, and topic correlation to explain the topic effects on influence diffusion fully. Meanwhile, the operator-based approach inherits the advantages of the heat diffusion-based model and the agent-based model. Accordingly, the OMT is recognized as a user context-aware and topic-aware prediction model, which can improve the practicability, quality, and simulation of influence diffusion modelling in multi-topic social networks. In the experiments, real-world datasets are adopted to evaluate the performance of the proposed OMT. The experimental results demonstrate that the OMT performs effectively in diffusion simulation and influence maximization.

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Authors and Affiliations

  1. University of Tasmania, Hobart, TAS, 7005, Australia

    Chenting Jiang, Shiqing Wu & Quan Bai

  2. Auckland University of Technology, Auckland, 1010, New Zealand

    Weihua Li

Authors
  1. Chenting Jiang
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  2. Weihua Li
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  3. Shiqing Wu
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  4. Quan Bai
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Corresponding author

Correspondence to Weihua Li .

Editor information

Editors and Affiliations

  1. School of Computer Science and Engineering, University of New South Wales, Sydney, Australia

    Wenjie Zhang

  2. Peking University, Beijing, China

    Lei Zou

  3. Zayed University, Dubai, United Arab Emirates

    Zakaria Maamar

  4. Swinburne University of Technology, Melbourne, VIC, Australia

    Lu Chen

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Jiang, C., Li, W., Wu, S., Bai, Q. (2021). OMT: An Operate-Based Approach for Modelling Multi-topic Influence Diffusion in Online Social Networks. In: Zhang, W., Zou, L., Maamar, Z., Chen, L. (eds) Web Information Systems Engineering – WISE 2021. WISE 2021. Lecture Notes in Computer Science(), vol 13080. Springer, Cham. https://doi.org/10.1007/978-3-030-90888-1_41

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  • DOI: https://doi.org/10.1007/978-3-030-90888-1_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90887-4

  • Online ISBN: 978-3-030-90888-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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