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Link Prediction Based on Heterogeneous Social Intimacy and Its Application in Social Influencer Integrated Marketing

Author

Listed:
  • Shugang Li

    (School of Management, Shanghai University, Shanghai 200444, China)

  • He Zhu

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Zhifang Wen

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Jiayi Li

    (Songjiang No. 2 Middle School, Shanghai 201600, China)

  • Yuning Zang

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Jiayi Zhang

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Ziqian Yan

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Yanfang Wei

    (School of Management, Shanghai University, Shanghai 200444, China)

Abstract

The social influencer integrated marketing strategy, which builds social influencers through potential users, has gained widespread attention in the industry. Traditional Scoring Link Prediction Algorithms (SLPA) mainly rely on homogeneous network indicators to predict friend relationships, which cannot provide accurate link prediction results in cold-start situations. To overcome these limitations, the Closeness Heterogeneous Link Prediction Algorithm (CHLPA) is proposed, which uses node closeness centrality to describe the social intimacy of nodes and provides a heterogeneous measure of a network based on this. Three types of heterogeneous indicators of social intimacy were proposed based on the principle of three-degree influence. Due to scarce overlapping node sample data, CHLPA uses gradient boosting trees to select the most suitable index, the second most suitable index, and the third most suitable index from Social Intimacy Heterogeneous Indexes (SIHIs) and SLPAs. Then, these indicators are weighted and combined to predict the likelihood of other node users in the two product circles in an online brand community becoming friends with overlapping node users. Finally, a hill-climbing algorithm is designed based on this to build integrated marketing social influencers, and the effectiveness and robustness of the algorithm are validated.

Suggested Citation

  • Shugang Li & He Zhu & Zhifang Wen & Jiayi Li & Yuning Zang & Jiayi Zhang & Ziqian Yan & Yanfang Wei, 2023. "Link Prediction Based on Heterogeneous Social Intimacy and Its Application in Social Influencer Integrated Marketing," Mathematics, MDPI, vol. 11(13), pages 1-19, July.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:13:p:3023-:d:1188944
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    References listed on IDEAS

    as
    1. Shugang Li & Ziming Wang & Beiyan Zhang & Boyi Zhu & Zhifang Wen & Zhaoxu Yu, 2022. "The Research of “Products Rapidly Attracting Users” Based on the Fully Integrated Link Prediction Algorithm," Mathematics, MDPI, vol. 10(14), pages 1-19, July.
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