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An Influence Maximization Algorithm for Dynamic Social Networks Based on Effective Links.

Baojun Fu1,2, Jianpei Zhang1, Hongna Bai2

  • 1College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China.

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|July 27, 2022
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Summary
This summary is machine-generated.

This study introduces a new algorithm to improve influence maximization in dynamic social networks by considering user interaction timing. The Outdegree Effective Link (OEL) algorithm enhances information diffusion efficiency and reduces computational complexity.

Keywords:
dynamic social networkseffective linkindependent cascade modelinfluence maximization

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Area of Science:

  • Network Science
  • Computational Social Science
  • Information Dissemination

Background:

  • Static social network structures are crucial for research but often overlook user interaction timeliness.
  • Traditional influence maximization methods struggle with dynamic networks, leading to inefficient information diffusion and high computational costs.
  • Understanding user interaction dynamics is key for effective influence maximization in social networks.

Purpose of the Study:

  • To analyze the impact of node interactions in dynamic social networks on information dissemination.
  • To extend the independent cascade model for dynamic social network analysis.
  • To propose an efficient influence maximization algorithm for dynamic social networks.

Main Methods:

  • Extended the classical independent cascade model to a dynamic social network dissemination model.
  • Developed a two-stage influence maximization algorithm (Outdegree Effective Link - OEL) utilizing node degree and effective links.
  • Compared OEL with five other influence maximization methods on four real-world datasets.

Main Results:

  • The proposed OEL algorithm demonstrates superior performance in terms of propagation range compared to existing methods.
  • OEL significantly improves the efficiency of influence maximization, showing reduced running times.
  • The algorithm effectively addresses the limitations of ignoring user interaction timeliness in traditional approaches.

Conclusions:

  • The Outdegree Effective Link (OEL) algorithm offers an effective solution for influence maximization in dynamic social networks.
  • Considering effective links and node degree enhances information dissemination efficiency and computational performance.
  • OEL provides a valuable tool for applications like product promotion, epidemic control, and public opinion monitoring.