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International Conference on Algorithmic Applications in Management

AAIM 2021: Algorithmic Aspects in Information and Management pp 240–251Cite as

Multi-attribute Based Influence Maximization in Social Networks

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 13153))

Abstract

Viral marketing on social networks is an important application and hot research problem. Most of the related work on viral marketing focuses on the spread of single information, while a product may associate with multi-attribute in real life. Information on multiple attributes of a product propagates in the social networks simultaneously and independently. The attribute information that a user receives will determine whether he would purchase the product or not. We extend the traditional single information influence maximization problem to the Multi-attribute based Influence Maximization Problem (MIMP). We present the Multi-dimensional IC model (MIC model) for the proposed problem. The objective function for MIMP is proved to be non-submodular, then we solve the problem with the Sandwich Algorithm, which can get a \(\max \left\{ \frac{f(S_U)}{\overline{f}(S_U)}, \frac{\underline{f}(S_L^*)}{ f(S_o^*)}\right\} (1-1/e)\) approximation ratio to the optimal solution. Experiments are conducted in two real world datasets to verify the correctness and effectiveness of the proposed algorithm.

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Author information

Authors and Affiliations

  1. School of Computers, Guangdong University of Technology, Guangzhou, 510006, China

    Qiufen Ni

  2. BNU-UIC Institute of Artificial Intelligence and Future Networks, Beijing Normal University at Zhuhai, Zhuhai, 519087, Guangdong, China

    Jianxiong Guo

  3. Guangdong Key Lab of AI and Multi-Modal Data Processing, BNU-HKBU United International College, Zhuhai, 519087, Guangdong, China

    Jianxiong Guo

  4. Accounting and Information Systems Department, Rutgers University, Piscataway, NJ, 08854, USA

    Hongmin W. Du

Authors
  1. Qiufen Ni
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  2. Jianxiong Guo
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  3. Hongmin W. Du
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Corresponding author

Correspondence to Jianxiong Guo .

Editor information

Editors and Affiliations

  1. The University of Texas at Dallas, Richardson, TX, USA

    Weili Wu

  2. Harbin Institute of Technology, Shenzhen, China

    Hongwei Du

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Ni, Q., Guo, J., Du, H.W. (2021). Multi-attribute Based Influence Maximization in Social Networks. In: Wu, W., Du, H. (eds) Algorithmic Aspects in Information and Management. AAIM 2021. Lecture Notes in Computer Science(), vol 13153. Springer, Cham. https://doi.org/10.1007/978-3-030-93176-6_21

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  • DOI: https://doi.org/10.1007/978-3-030-93176-6_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-93175-9

  • Online ISBN: 978-3-030-93176-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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