MATLAB Code Implementation for Simulation

Simulation programs are computer applications designed to replicate real-world scenarios for analysis and understanding. This particular implementation models the Competitive Propagation (CP) process using the SIR (Susceptible-Infected-Recovered) information diffusion framework. The SIR model adapts epidemiological dynamics to information propagation, helping researchers understand dissemination patterns and velocity within populations. The MATLAB implementation typically utilizes differential equations with Euler method or ODE solvers (ode45) to simulate state transitions between susceptible, infected, and recovered nodes. Key parameters include infection rate (β), recovery rate (γ), and initial infected population proportion. The code structure generally involves: 1) Initialization of population states and parameters 2) Time-loop iterations with state update equations 3) Visualization of propagation curves using plot functions Through adjustable parameter configurations, the simulation can replicate diverse scenarios, enabling improved prediction of information spread trends. The implementation may incorporate adjacency matrices for network-based diffusion or use mean-field approximations for homogeneous mixing populations.