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Interactive social contagions and co-infections on complex networks
Quan-Hui Liu1, Lin-Feng Zhong1, Wei Wang1
1Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
Chaos (Woodbury, N.Y.)
|February 3, 2018
Summary
This study introduces a model for sequential social behavior spread on networks. We found that the first behavior can inhibit or synergize the second, altering its spread dynamics and phase transitions.
Area of Science:
- Complex systems science
- Network science
- Sociophysics
Background:
- Interactions among multiple social contagion processes on complex networks challenge existing theoretical frameworks.
- Understanding sequential behavior spread is crucial for social dynamics.
Purpose of the Study:
- To propose an interactive social behavior spreading model for sequential contagions.
- To investigate how the first behavior affects the spread and phase transitions of the second behavior.
Main Methods:
- Developed a model for sequential spread of two behaviors on a complex network.
- Utilized an edge-based compartmental method for theoretical analysis.
- Validated theoretical predictions with simulation results.
Main Results:
- The inhibiting effect of the first behavior can shift the second behavior's continuous phase transition to discontinuous.
- Synergistic effects of the first behavior can revert discontinuous transitions to continuous, facilitating adoption.
- Synergy enlarges the co-existence region for both behaviors.
Conclusions:
- The proposed model provides insights into the complex interplay of sequential social contagions.
- Findings highlight the significant impact of prior behavior on subsequent adoption dynamics.
- This research offers a theoretical basis for understanding interactive social behavior spread in human societies.
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