Analyze a Person-to-Person Network

Hi VI_Migration  - this is a great question, and actually can be a great addition to the documentation examples!

The plots on `igraph` can be best customized with a combination of `ggplot2` and `ggraph`. Here is a simple code example, where this effectively asks `network_p2p()` to export an igraph object and then customize a graph from "scratch" with the `ggplot2` and `ggraph` libraries: 

# Load libraries
library(wpa)
library(tidyverse)
library(ggraph)

# Simulate a small person-to-person dataset
p2p_data <- p2p_data_sim(size = 50)

# Return a network igraph object
p2p_g <-
  p2p_data %>%
  network_p2p(display = "louvain",
              return = "network")

# Custom chart using `ggplot2` + `ggraph`
p2p_g %>%
  ggraph::ggraph(layout = "igraph", algorithm = "mds") +
  ggraph::geom_edge_link(colour = "lightgrey", edge_width = 0.05, alpha = 1) +
  ggraph::geom_node_point(aes(colour = !!sym("cluster")),
                          alpha = 0.7,
                          pch = 16) +
  scale_color_manual(values = c("red", "green", "black")) +
  theme_void() +
  theme(
    legend.position = "bottom",
    legend.background = element_rect(fill = "white", colour = "white"),
    
    text = element_text(colour = "black"),
    axis.line = element_blank(),
    panel.grid = element_blank()
  ) +
  labs(caption = paste0("Person to person collaboration example"), # spaces intentional
       y = "",
       x = "")

This code chunk generates a chart like the below, where the colours have been custom-defined. Since this is `ggplot2`, you can customize the colours in any way you want: 

The slight disadvantage would the `ggraph` method is that it'll be more intensive to compute for large graphs. However, this may provide a workaround if you test the visualization first with a small graph subset before running it on more data. Does this help? (There could be alternative solutions, but this is the most straightforward one I can think of)