Computer Science ›› 2020, Vol. 47 ›› Issue (7): 141-153.doi: 10.11896/jsjkx.200300130

• Artificial Intelligence • Previous Articles     Next Articles

Review of Information Cascade Prediction Methods Based on Deep Learning

ZHANG Zhi-yang, ZHANG Feng-li, TAN Qi, WANG Rui-jin   

  1. School of Information and Software Engineering,University of Electronic Science and Technology of China,Chengdu 610054,China
  • Received:2020-03-23 Online:2020-07-15 Published:2020-07-16
  • About author:ZHANG Zhi-yang,born in 1997,postgraduate,is a member of China Computer Federation.His main research interests include machine learning,data mining and cascade prediction.
    ZHANG Feng-li,born in 1963,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.Her main research interests include network security and network engineering,cloud computing and big data and machine learning.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China(61802033,61472064,61602096),Sichuan Science and Technology Program (2018GZ0087,2019YJ0543),Sichuan Regional Innovation Cooperation Project(2020YFQ0018),Chinese Postdoctoral Science Foundation(2018M643453), Guangdong Provincial Key Laboratory Project(2017B030314131) and Network and Data Security Key Laboratory of Sichuan Province Open Issue(NDSMS201606)

Abstract: Online social media greatly promotes the generation and transmission of information,exacerbates the communication and interaction between massive amounts of information,and highlights the importance of predicting information cascades.In recent years,deep learning has been widely used in the field of information cascade prediction.This paper mainly classifies,sorts,and summarizes the current research status of deep learning-based information cascade prediction methods and classic algorithms.According to the different emphasis of information cascade feature characterization,the information cascade prediction method based on deep learning is divided into time series information cascade prediction method and topology information cascade prediction method.The time series information cascade prediction method is further divided into methods based on random walks and methods based on diffusion paths,and the topology information cascade prediction method is divided into methods based on global topological structure and methods based on neighborhood aggregation.This paper details the principles and advantages and disadvantages of each type of method,and introduces the data sets and evaluation indicators commonly used in the field of information cascade prediction,and compares the information cascade prediction algorithms based on deep learning in the macro and micro information cascade prediction scenarios,and discusses some technical details commonly used in information cascade prediction algorithms.Finally,this paper summarizes the field possible future research directions and development trends.

Key words: Cascade size prediction, Deep learning, Information cascade prediction, Node prediction, Online social media, Popularity prediction

CLC Number: 

  • TP183
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