Drop POS proportions
Change-Id: Id77b9471a82646e18ce6b0e253b11219afa153f9
diff --git a/R/poster.Rmd b/R/poster.Rmd
index 9ff9497..f75e2bf 100644
--- a/R/poster.Rmd
+++ b/R/poster.Rmd
@@ -147,37 +147,13 @@
legend.text = element_text(size = rel(1)))
```
-### Part-of-Speech proportions
-```{r pos_proportions, fig.width=14, fig.height=10, out.width = "100%"}
-POS_tag <- c(
- "ADJ", "ADP",# "PUNCT",
- "ADV", "AUX", # "SYM",
- # "INTJ",
- "CCONJ", # "X",
- "NOUN", "DET",
- "PROPN", #"NUM",
- "VERB", #"PART",
- "PRON",
- "SCONJ"
- )
+# Pilot study
-icc_by_pos_tag <- icc %>% expand_grid(POS = POS_tag) %>%
- rowwise() %>%
- mutate(f = frequencyQuery(icc_con(lang), sprintf("[ud/p=%s]", POS))$f)
+* Identification of Light Verb Constructions with *take*
+* in order to investigate the limitations imposed by the very small corpus sizes
+* using RKorapClient [@kupietz_rkorapclient_2020] to access corpora and get reproducible results of the collocation analysis
-icc_by_pos_tag %>% ggplot(aes(x=lang, fill = POS, y=f)) +
- geom_col() + scale_y_continuous(labels = label_number(scale_cut = cut_short_scale())) +
- scale_fill_ids() + scale_color_ids() +
- theme_ids(base_size=24) +
- theme(
- axis.title.x = element_text(size = rel(1.5), face = "bold"),
- axis.title.y = element_text(size = rel(1.5), face = "bold"),
- axis.text = element_text(size = rel(1)),
- legend.title = element_text(size = rel(1), face = "bold"),
- legend.text = element_text(size = rel(1))) +
- geom_text(aes(label=sprintf("%.2f%%", 100*f), y=f), position= position_stack(reverse = F, vjust = 0.5), color="black", size=6.2, family="Fira Sans Condensed")
-```
# Identification of Light Verb Constructions with *take*