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Adaptive bridge control strategy for opinion evolution on social networks.
Cheng Qian1, Jinde Cao, Jianquan Lu
1Department of Mathematics, Southeast University, Nanjing 210096, China. qianche@umich.edu
Chaos (Woodbury, N.Y.)
|July 5, 2011
Summary
We developed an adaptive bridge control (ABC) strategy to manage opinion dynamics in social networks. This efficient method controls "bridge" nodes without needing network structure details, proving effective across various network types.
Area of Science:
- Complex Networks
- Social Network Analysis
- Opinion Dynamics
Background:
- Controlling opinion dynamics in complex networks is crucial.
- Existing strategies often require detailed network knowledge (e.g., node degrees).
- There is a need for efficient control strategies that minimize information requirements.
Purpose of the Study:
- To introduce a novel adaptive bridge control (ABC) strategy for opinion dynamics in social networks.
- To evaluate the efficiency of the ABC strategy across different network topologies.
- To investigate the relationship between network clustering coefficient and the ABC strategy's performance.
Main Methods:
- Proposed a new high-order social network model for opinion dynamics.
- Developed an algorithm to identify and control 'bridge' nodes without global or local network information.
- Tested the ABC strategy on random, small-world, and scale-free networks, including those with adjusted clustering coefficients.
Main Results:
- The ABC strategy demonstrates efficiency across random, small-world, and scale-free networks.
- The strategy's effectiveness is closely correlated with the network's clustering coefficient.
- Higher clustering coefficients result in more efficient opinion control via the ABC strategy.
Conclusions:
- The proposed ABC strategy offers an efficient method for controlling opinion dynamics in complex social networks.
- The ABC strategy's performance is superior in networks with higher clustering coefficients.
- This approach provides a valuable tool for managing social network behavior without extensive data requirements.
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