diffusion_exercise.qmd

---
title: "Diffusion Exercise"
---

Create a diffusion network model which simulates the diffusion of a rumor 
throughout the UKfaculty population of size n = 81. Use set.seed(2223).  
```{r}
set.seed(2223)

# First, load in the dataset
library(igraph)
data(UKfaculty, package="igraphdata")
n <- igraph::vcount(UKfaculty)

# Turning the network into an edgelist
library(epiworldR)
UKfaculty_vertex_data <- as_data_frame(UKfaculty, what = c("vertices"))
UKfaculty_matrix <- as.matrix(UKfaculty_vertex_data)
UKfaculty_edgelist <- as_edgelist(UKfaculty)
library(netplot)
nplot(UKfaculty)

# Simulate a 2 col numeric matrix and use for data in next function
# Creating the diffusion model
adopt_rumor <- ModelDiffNet(
  "Rumor",
  prevalence = .05,
  prob_adopt = .1,
  data       = UKfaculty_matrix,
  params     = c(1, 4)
)

g <- matrix(runif(n ^ 2) < .01, nrow = n)
diag(g) <- FALSE
el <- which(g, arr.ind = TRUE) - 1L

# Simulating a population from smallworld - Use agents_from_edgelist
agents_from_edgelist(adopt_rumor,
                     source = el[,1],
                     target = el[,2],
                     size = n, 
                     directed = TRUE)

# Running the model for 50 steps
run(adopt_rumor, 50)

# Plotting the model
plot(adopt_rumor)
```