R helper function for topic modeling

topic-helper.R

analyzeTopics <- function(ctmFit,fileLoc){
  td_beta <- tidy(ctmFit, matrix = "beta")
  
  # helper functions (from David Robinson's R Package)
  scale_x_reordered <- function(..., sep = "___") {
    reg <- paste0(sep, ".+$")
    ggplot2::scale_x_discrete(labels = function(x) gsub(reg, "", x), ...)
  }
  
  reorder_within <- function(x, by, within, fun = mean, sep = "___", ...) {
    new_x <- paste(x, within, sep = sep)
    stats::reorder(new_x, by, FUN = fun)
  }
  
  # Examine the topics
  td_beta %>%
    group_by(topic) %>%
    top_n(8, beta) %>%
    ungroup() %>%
    mutate(topic = paste0("Topic ", topic),
           term = reorder_within(term, beta, topic)) %>%
    ggplot(aes(term, beta, fill = topic)) +
    geom_col(alpha = 0.8, show.legend = FALSE) +
    facet_wrap(~ topic, ncol = 4, scales = "free") +
    scale_x_reordered() +
    coord_flip() +
    labs(x = "",
         y = "")
  
  #saveing the plot
  ggsave(fileLoc)
  
  
}