Analyzing Information Cascading in Large Scale Networks: A Fixed Point Approach-Reference-Cited by-同舟云学术

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Analyzing Information Cascading in Large Scale Networks: A Fixed Point Approach

Published:2024-10 Issue:10 Volume:23 Page:10060-10076
ISSN:1536-1233
Container-title:IEEE Transactions on Mobile Computing
language:
Short-container-title:IEEE Trans. on Mobile Comput.

Author:

Fu Luoyi¹^ORCID,Xu Jiasheng²^ORCID,Zhou Lei³^ORCID,Wang Xinbing²^ORCID,Zhou Chenghu⁴^ORCID

Affiliation:

1. Department of Computer Science, Engineering, Shanghai Jiao Tong University, Shanghai, China

2. Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China

3. School of Oceanography, Shanghai Jiao Tong University, Shanghai, China

4. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

Funder

NSF China

Shanghai Pilot Program for Basic Research - Shanghai Jiao Tong University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7755/10663873/10460143.pdf?arnumber=10460143

Reference39 articles.

1. DRIMUX: Dynamic Rumor Influence Minimization with User Experience in Social Networks

2. Maximizing the spread of influence through a social network

3. Sketch-based Influence Maximization and Computation

4. LIDDE: A differential evolution algorithm based on local-influence-descending search strategy for influence maximization in social networks

5. Efficient influence maximization in social networks

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