CKS: A Community-Based K-shell Decomposition Approach Using Community Bridge Nodes for Influence Maximization (Student Abstract)

Authors

  • Inder Khatri Biometric Research Laboratory, Delhi Technological University
  • Aaryan Gupta Delhi Technological University
  • Arjun Choudhry Biometric Research Laboratory, Delhi Technological University
  • Aryan Tyagi Delhi Technological University
  • Dinesh Kumar Vishwakarma Biometric Research Laboratory, Delhi Technological University
  • Mukesh Prasad School of Computer Science, University of Technology Sydney

DOI:

https://doi.org/10.1609/aaai.v37i13.26980

Keywords:

Complex Networks, Influence Maximisation, Community Structures, Bridge Nodes, Entropy, Online Social Networks, Independent Cascades

Abstract

Social networks have enabled user-specific advertisements and recommendations on their platforms, which puts a significant focus on Influence Maximisation (IM) for target advertising and related tasks. The aim is to identify nodes in the network which can maximize the spread of information through a diffusion cascade. We propose a community structures-based approach that employs K-Shell algorithm with community structures to generate a score for the connections between seed nodes and communities. Further, our approach employs entropy within communities to ensure the proper spread of information within the communities. We validate our approach on four publicly available networks and show its superiority to four state-of-the-art approaches while still being relatively efficient.

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Published

2024-07-15

How to Cite

Khatri, I., Gupta, A., Choudhry, A., Tyagi, A., Vishwakarma, D. K., & Prasad, M. (2024). CKS: A Community-Based K-shell Decomposition Approach Using Community Bridge Nodes for Influence Maximization (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16240-16241. https://doi.org/10.1609/aaai.v37i13.26980