Computer Science ›› 2024, Vol. 51 ›› Issue (1): 99-112.doi: 10.11896/jsjkx.230500127

• Database & Big Data & Data Science • Previous Articles     Next Articles

Survey of Inferring Information Diffusion Networks

WANG Yuchen1, GAO Chao1, WANG Zhen1,2   

  1. 1 School of Artificial Intelligence,OPtics and ElectroNics(iOPEN),Northwestern Polytechnical University,Xi’an 710072,China
    2 School of Cybersecurity,Northwestern Polytechnical University,Xi’an 710072,China
  • Received:2023-05-01 Revised:2023-10-07 Online:2024-01-15 Published:2024-01-12
  • About author:WANG Yuchen,born in 1999,postgra-duate.His main research interests include data mining and complex network analysis.
    GAO Chao,born in 1980,Ph.D,professor,Ph.D supervisor.His main research interests include artificial intelligence theory,social computing,system simulation,big data analysis,etc.
  • Supported by:
    National Key R & D Program of China(2022YFE0112300) and National Natural Science Foundation of China(62261136549,61976181).

Abstract: Information diffusion can be modeled as a stochastic process over a network.However,the topology of an underlying diffusion network and the pathways of spread are often not visible in real-world scenarios.Therefore,the inference of diffusion networks becomes critical in the analysis and understanding of the diffusion process,tracking the pathways of spread,and even predicting future contagion events.There has been a surge of interest in diffusion network inference over the past few years.This paper investigates and summarizes the representative research in the field of diffusion network inference.Finally,this paper analyzes the existing problems of diffusion network inference and provides a new perspective on this field.

Key words: Diffusion network, Network inference, Information diffusion, Information cascades, Relationship inference

CLC Number: 

  • TP181
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