yehzee.R

library(tidyverse)
library(tidygraph)
library(netmediate)

data <- read_csv("final_regime.IGO.sanction.csv") |> 
  # remove some columns of missing data to avoid downstream issues
  select(-1, -AMCOW, -MOPAN)

node_data <- data |> 
  select(country, ccode, polity2, democracy, sanction)

incidence <- data |> 
  select(-country, -ccode, -polity2, -democracy, -sanction) |> 
  as.matrix()

rownames(incidence) <- data$country

# setting up the data

graph <- incidence |> 
  igraph::graph_from_incidence_matrix() |> 
  as_tbl_graph() |> 
  activate(nodes) |> 
  left_join(node_data, by = c("name" = "country")) |> 
  activate(edges) |> 
  mutate(
    weight = 1
  )

# getting and plotting estimates

# unclear to me if trt should be as.factor(polity2) or polity2
# also unclear to me how sanction should be coded

curve <- graph |> 
  activate(nodes) |> 
  sensitivity_curve(
    sanction ~ as.factor(polity2),  
    max_rank = 10,
    ranks_to_consider = 5,
    coembedding = "U"
  )

plot(curve) +
  theme_classic()

# checking the quality of the embeddings

library(vsp)

fa <- incidence |> 
  as("CsparseMatrix") |> 
  vsp(rank = 10)

plot_ipr_pairs(fa)

fa |> 
  get_varimax_y() |>
  dplyr::select(-id) |>
  GGally::ggpairs(ggplot2::aes(alpha = 0.001)) +
  ggplot2::theme_minimal()

fa |> 
  get_varimax_z() |>
  dplyr::select(-id) |>
  GGally::ggpairs(ggplot2::aes(alpha = 0.001)) +
  ggplot2::theme_minimal()

# embeddings seem possibly okay but certainly not great