updating some of the scripts for PCA analysis

p2/quest/neurobiber_PCA_analysis.R

@@ -59,6 +59,7 @@ neurobiber_subcomment_pca_df$comment_type <- "subcomment"
 #clean the messages 
 neurobiber_description_pca_df$cleaned_comment <- sapply(neurobiber_description_pca_df$text, preprocess_comment)
 neurobiber_subcomment_pca_df$cleaned_comment <- sapply(neurobiber_subcomment_pca_df$text, preprocess_comment)
+total_joined$cleaned_comment <- sapply(total_joined$text, preprocess_comment)
 
 subcomment_joined <- subcomment_joined %>%
   mutate(pair_in_description = (paste(AuthorPHID, TaskPHID) %in%
@@ -77,13 +78,13 @@ discussion_anova_results <- neurobiber_subcomment_pca_df %>%
 discussion_anova_results
 
 # look at the representative comments for PC1 and PC2
-top5 <- neurobiber_description_pca_df %>%
-  arrange(desc(PC2)) %>%
+top5 <- total_joined %>%
+  arrange(desc(PC4)) %>%
   slice(300:310) %>%
   pull(cleaned_comment)
 
-bottom5 <- neurobiber_description_pca_df %>%
-  arrange(PC2) %>%
+bottom5 <- total_joined %>%
+  arrange(PC4) %>%
   slice(300:310) %>%
   pull(cleaned_comment)
 
@@ -130,18 +131,17 @@ description_sampled_authors <- description_joined %>%
 description_sub_sample <- description_joined %>%
   filter(AuthorPHID %in% description_sampled_authors)
 
-ggplot(description_sub_sample, aes(x = PC2, y = PC1, fill = AuthorPHID)) +
+ggplot(total_joined, aes(x = PC4, y = PC3, fill = comment_type)) +
   facet_grid(source~phase, scales="fixed") +
   geom_point(shape = 21, alpha=0.3, size=2) +
   xlim(-30, 30) + 
   ylim(-30, 30) +
-  scale_fill_brewer(palette = "Set1") +
+  scale_fill_viridis_d() +
   theme_minimal() +
-  guides(fill = "none") + 
   labs(
     title = "PCs for Task Comments (Faceted by source and phase)",
-    x = "PC2",
-    y = "PC1",
+    x = "PC4",
+    y = "PC3",
   )
 
 priority_order <- c("Unbreak Now!", "High", "Medium", "Low", "Lowest", "Needs Triage")
@@ -153,18 +153,18 @@ description_joined <- description_joined %>%
   mutate(priority = factor(priority.y, levels = priority_order))
 
 ggplot(total_joined, aes(
-  x = PC1,    # x-axis grouping
-  y = PC2,
-  fill = comment_type
+  x = as.factor(comment_type),    # x-axis grouping
+  y = PC3,
+  fill = isAuthorWMF
 )) +
-  ylim(-20, 20) +
+  ylim(-30, 30) +
   geom_boxplot(alpha = 0.7, position = position_dodge(width = 0.9)) +
   facet_grid(. ~ source, scales = "fixed") +   # Facet by source; adjust as needed
   scale_fill_viridis_d() +
   theme_minimal() +
   labs(
-    title = "Boxplot of PC2 for Task Descriptions",
-    x = "Task priority",
-    y = "PC2",
+    title = "Boxplot of PC4",
+    x = "Comment_type",
+    y = "PC4",
     fill = "isAuthorWMF?"
   )