```{r}
library(Rdimtools)
library(tidytext)
library(scales)
words_emb_matrix = as.matrix(unnested_words[,2:32])
pca_res <- do.pca(words_emb_matrix, ndim=16)

res = pca_res$Y %>% rescale(to=c(-1, 1)) %>% as_tibble()
res$word = deduped_words$word
res %>%
  pivot_longer(!word, names_prefix="V", names_to="pca", names_transform =list(pca=as.integer)) %>%
  group_by(pca) %>%
  top_n(12, abs(value)) %>%
  ungroup() %>%
  mutate(word = reorder_within(word, value, pca)) %>%
  ggplot(aes(word, value, fill=pca)) + 
  geom_col(alpha=0.8, show.legend = FALSE) +
  facet_wrap(~pca, scales = "free_y", ncol = 4) + 
  scale_x_reordered() +
  coord_flip() +
  labs(
    x = NULL,
    y = "Value"
  )
```
```{r}
g2 <- res[1:200,] %>% ggplot(aes(x=V1, y=V2, label=word)) + geom_text(aes(label=word), hjust=0, vjust=0, color="blue")
ggplotly(g2, tooltip = 'word')
```