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Social contagions on interdependent lattice networks
Panpan Shu1, Lei Gao2, Pengcheng Zhao3
1School of Sciences, Xi'an University of Technology, Xi'an, 710054, China.
Scientific Reports
|March 17, 2017
Summary
This study models social contagion on interdependent spatial networks. Increasing dependency links boosts contagion but can alter phase transitions from second-order to first-order.
Area of Science:
- Complex systems
- Network science
- Social dynamics
Background:
- Research on interdependent spatial networks is growing.
- Understanding social contagion dynamics on these networks is limited.
Purpose of the Study:
- To introduce a non-Markovian social contagion model on interdependent spatial networks.
- To investigate the influence of dependency links on contagion dynamics and phase transitions.
Main Methods:
- Developed a novel non-Markovian social contagion model.
- Utilized two identical two-dimensional lattices for network structure.
- Employed finite-size analysis to determine phase transition types.
Main Results:
- Higher dependency link density increases the final recovered nodes.
- Increasing dependency links shifts phase transitions from second-order to first-order.
- Initial adopted node fraction influences phase transition order in strongly interdependent networks.
Conclusions:
- Interdependent spatial networks significantly impact social contagion.
- Dependency link density and initial adoption rates are critical factors in contagion dynamics and phase transitions.
- The study provides insights into the complex interplay between network structure and social behavior.
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