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Related Experiment Video

Updated: Aug 30, 2025

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading

Published on: May 22, 2021

Distinct spreading patterns induced by coexisting channels in information spreading dynamics.

Jiao Wu¹, Kesheng Xu², Xiyun Zhang³

¹School of Mathematical Sciences, Jiangsu University, Zhenjiang, Jiangsu 212013, China.

Chaos (Woodbury, N.Y.)

|September 1, 2022

Summary

New communication channels impact information spread dynamics. This study reveals three outbreak patterns—localized, delayed, and synchronized—based on network layer coupling strength, offering insights into real-world information diffusion.

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Area of Science:

Network Science
Information Dynamics
Computational Social Science

Background:

Modern communication channels significantly alter information dissemination.
The influence of these channels on information spreading dynamics, particularly outbreak patterns, remains underexplored.

Purpose of the Study:

To investigate information spreading patterns in a two-layered network with coexisting intra- and inter-layer communication channels.
To analyze how inter-layer coupling strength affects outbreak behaviors.

Main Methods:

Utilized a susceptible-accepted-recovered (SAR) model.
Examined information spreading in a two-layered network structure.
Varied inter-layer coupling strength, including average node degree and transmission probability.

Main Results:

Identified three distinct spreading patterns: localized (weak coupling), two-peak with time-delay (intermediate coupling), and synchronized (strong coupling).
Demonstrated that high transmission probability can compensate for low average degree, promoting inter-layer spread.
Discovered a critical average degree that decreases as a power law with increasing transmission probability.
Observed a phase space gap near the critical inter-layer average degree, indicating potential for global outbreaks.

Conclusions:

Inter-layer coupling strength is a critical factor determining information outbreak patterns in multi-channel networks.
Transmission probability plays a significant role in facilitating cross-layer information diffusion.
Findings provide a framework for understanding complex information spreading behaviors in real-world scenarios.