Epidemic Model-based Network Influential Node Ranking Methods: A Ranking Rationality Perspective
Article No.: 203, Pages 1 - 39
Abstract
Existing surveys and reviews on Influential Node Ranking Methods (INRMs) have primarily focused on technical details, neglecting thorough research on verifying the actual influence of these nodes in a network. This oversight may result in erroneous rankings. In this survey, we address this gap by conducting an extensive analysis of 82 primary studies related to INRMs based on the epidemic model over the past 20 years. We statistically analyze and categorize benchmark networks into four types, and conclude that high-quality networks with complete information are insufficient and most INRMs only focus on undirected and unweighted networks, which encourages collaboration between industry and academia to provide optimized networks. Additionally, we categorize and discuss the strengths, weaknesses, and optimized crafts of seven categories of INRMs, helping engineers and researchers narrow down their choices when selecting appropriate INRMs for their specific needs. Furthermore, we define the Capability and Correctness metrics and utilize their usage frequency and functionality to assist engineers and researchers in prioritizing and selecting suitable metrics for different INRMs and networks. To our knowledge, this is the first survey that systematically summarizes the Capability and Correctness of INRMs, providing insights for the complex network community and aiding INRM selection and evaluation.
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Index Terms
- Epidemic Model-based Network Influential Node Ranking Methods: A Ranking Rationality Perspective
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Published In
August 2024
963 pages
ISSN:0360-0300
EISSN:1557-7341
DOI:10.1145/3613627
- Editors:
- David Atienza,
- Michela Milano
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Association for Computing Machinery
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Publication History
Published: 26 April 2024
Online AM: 19 March 2024
Accepted: 10 March 2024
Revised: 23 January 2024
Received: 21 March 2023
Published in CSUR Volume 56, Issue 8
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- S&T Program of Hebei
- Natural Science Foundation of Hebei Province
- Science Research Project of Hebei Education Department
- National Research Foundation, Singapore
- Infocomm Media Development Authority
- Future Communications Research & Development Programme
- DSO National Laboratories under the AI Singapore Programme
- MOE Tier 1
- National Natural Science Foundation of China
- Foundation of State Key Laboratory of Public Big Data
- National Key Research and Development Program of China
- Guizhou Provincial Science and Technology Projects
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