Influential nodes identification in complex networks: a comprehensive literature review

Area of Science:

• Network Science
• Computational Social Science

Background:

• Complex networks are a rapidly evolving field of significant scientific and innovative interest.
• Detecting influential nodes within these networks presents a key research challenge.

Purpose of the Study:

• To provide a comprehensive overview of complex networks.
• To detail key concepts in network measurements, structure, and social influence.
• To present a state-of-the-art review of influential node detection approaches.

Main Methods:

• Literature review of complex network theory.
• Analysis of network metrics, topology evolution, and dynamics.
• Detailed examination of existing influential node identification methods.

Main Results:

• Summarized fundamental metrics and topological changes in complex networks over time.
• Evaluated the strengths and weaknesses of various influential node detection techniques.
• Provided a foundational literature base for researchers entering the field.

Conclusions:

• Complex network research is a dynamic and growing area.
• Understanding network structure and influence is crucial for various applications.
• Further research into influential node detection methods is warranted.