The function to create lda wordclouds

ldaWordclouds(
  model,
  test,
  color_negative_cor = scale_color_gradient(low = "darkgreen", high = "green"),
  color_positive_cor = scale_color_gradient(low = "darkred", high = "red"),
  scale_size = FALSE,
  plot_topics_idx = NULL,
  p_threshold = 0.05,
  save_dir = "./results",
  figure_format = ".svg",
  seed = 42
)

Arguments

model

(list) The trained model

test

(list) The test results

color_negative_cor

(R_obj) The color gradient for negative correlations

color_positive_cor

(R_obj) The color gradient for positive correlations

scale_size

(logical) Whether to scale the size of the words

plot_topics_idx

(vector) The topics to plot determined by index

p_threshold

(integer) The p-value threshold to use for significance

save_dir

(string) The directory to save the wordclouds

figure_format

(string) Set the figure format, e.g., .svg, or .png.

seed

(integer) The seed to set for reproducibility

Value

nothing is returned, the wordclouds are saved in the save_dir