Modeling and Analysis of Delayed Matthew Effect in Social Systems via $k$-Winners-Take-All Network

A new time-delayed Matthew effect model is developed in this paper, aiming to depict the Matthew effect in social systems. Based on the construction of a social network with information transmission delay, the development speed and development potential of each agent in the social network are defined as some specific parameters, and these parameters are used to describe the status and evolutionary trend of each agent. Furthermore, this paper theoretically derives the value of the maximum time delay allowed by the proposed time-delayed Matthew effect model in a social network and verifies its convergence. Through a series of simulations, the correctness and feasibility of the proposed model are demonstrated. This work takes the time delay in information transmission into account in the Matthew effect model for the first time so that the model is capable of describing this social phenomenon accurately.

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Publication Details

Journal
IEEE Transactions on Network Science and Engineering
Published
2025-04-22
DOI
https://doi.org/10.1109/tnse.2025.3562075
Citations
4
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
5.29
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article

Modeling and Analysis of Delayed Matthew Effect in Social Systems via $k$-Winners-Take-All Network

Suibing Li, Long Jin, Junqiang Wang, Shuai Li
4 citations
IEEE Transactions on Network Science and Engineering
Complex Network Analysis Techniques
5.29
article

Modeling and Analysis of Delayed Matthew Effect in Social Systems via $k$-Winners-Take-All Network

Suibing Li, Long Jin, Junqiang Wang, Shuai Li
article en
4 citations

Abstract

A new time-delayed Matthew effect model is developed in this paper, aiming to depict the Matthew effect in social systems. Based on the construction of a social network with information transmission delay, the development speed and development potential of each agent in the social network are defined as some specific parameters, and these parameters are used to describe the status and evolutionary trend of each agent. Furthermore, this paper theoretically derives the value of the maximum time delay allowed by the proposed time-delayed Matthew effect model in a social network and verifies its convergence. Through a series of simulations, the correctness and feasibility of the proposed model are demonstrated. This work takes the time delay in information transmission into account in the Matthew effect model for the first time so that the model is capable of describing this social phenomenon accurately.

IEEE Transactions on Network Science and EngineeringVol. 12(5)
Institute of Electronics (CN), University of Chinese Academy of Sciences (CN), Lanzhou University (CN)
Openalex Percentile: Top 5%
Complex Network Analysis Techniques
5.29
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