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The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
Published on: October 20, 2022
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Game-theoretical approach for opinion dynamics on social networks
Zhifang Li1, Xiaojie Chen1, Han-Xin Yang2
1School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.
Chaos (Woodbury, N.Y.)
|July 30, 2022
Summary
This study introduces an evolutionary game model to understand opinion spreading on social networks. It reveals that an opinion
Area of Science:
- Complex Systems
- Social Network Analysis
- Game Theory
Background:
- Opinion dynamics on social networks are a growing research area.
- Limited theoretical work exists on the conditions for widespread opinion adoption.
- Existing models often overlook the non-random nature of opinion selection.
Purpose of the Study:
- To develop an evolutionary game model for binary opinions.
- To theoretically analyze the conditions enabling an opinion to spread throughout a population.
- To investigate how public knowledge and neighbor interactions influence opinion choice.
Main Methods:
- Utilized an evolutionary game approach for a binary opinion model.
- Incorporated agent opinion choice based on public knowledge and neighbor interactions.
- Employed coalescing random walks to derive spreading conditions in the weak selection limit.
Main Results:
- Derived a condition for opinion A to spread successfully on social networks.
- Spreading success depends on opinion scores, feedback, and network structure (edge weights, degrees).
- Isolated the impact of public information and feedback interactions on opinion vitality.
Conclusions:
- The model provides a theoretical framework for understanding opinion spread.
- Network structure and individual interaction dynamics significantly influence opinion propagation.
- Findings are validated through simulations on various network types (fully connected, small-world, scale-free).
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