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Deep Learning in Social Networks

In: Computational Aspects of Social Networks

Author

Listed:
  • Weili Wu

    (University of Texas at Dallas, Department of Computer Science)

  • Zhao Zhang

    (Zhejiang Normal University, School of Mathematics)

  • Ding-Zhu Du

    (University of Texas at Dallas, Department of Computer Science)

Abstract

An important class of graph data is the social data, generated from online social networks (OSNs). The social data have been growing rapidly over the internet through various OSNs, including online websites (such as Facebook, LinkedIn, and ResearchGate) and messengers (such as Skype). The widespread use of them leads to an increasing interest in efficiently and correctly discovering important, useful, and implicit information. Efficient techniques for data harnessing about social data are crucial to applications across many domains, including public safety, environment management, election, and viral marketing.

Suggested Citation

  • Weili Wu & Zhao Zhang & Ding-Zhu Du, 2026. "Deep Learning in Social Networks," Springer Optimization and Its Applications, in: Computational Aspects of Social Networks, chapter 0, pages 333-353, Springer.
    • Handle: RePEc:spr:spochp:978-3-032-14833-9_11
    DOI: 10.1007/978-3-032-14833-9_11
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