Abstract
We consider the diffusion of two alternatives in social networks using a game-theoretic approach. Each individual plays a coordination game with its neighbors repeatedly and decides which to adopt. As products are used in conjunction with others and through repeated interactions, individuals are more interested in their long-term benefits and tend to show trust to others to maximize their long-term utility by choosing a suboptimal option with respect to instantaneous payoff. To capture such trust behavior, we deploy limited-trust equilibrium (LTE) in diffusion process. We analyze the convergence of emerging dynamics to equilibrium points using mean-field approximation and study the equilibrium state and the convergence rate of diffusion using absorption probability and expected absorption time of a reduced-size absorbing Markov chain. We also show that the diffusion model on LTE under the best-response strategy can be converted to the well-known linear threshold model. Simulation results show that when agents behave trustworthy, their long-term utility will increase significantly compared to the case when they are solely self-interested. Moreover, the Markov chain analysis provides a good estimate of convergence properties over random networks.
Original language | English (US) |
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Pages (from-to) | 1320-1336 |
Number of pages | 17 |
Journal | IEEE Transactions on Network Science and Engineering |
Volume | 11 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2024 |
Keywords
- Diffusion dynamics
- Markov chains
- game theory
- limited-trust equilibrium
- social networks
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Computer Networks and Communications