bla

full_data.csv

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c989a986e4ca0d8fd3bfcbfa49b58a04a28e2b16a88271c5f8ef28fe10c461eb
-size 1050676452
+oid sha256:9fec1f45e6d895ed85cb6194f2deef78ffec33d6cf64bf6af4580718db20fd0d
+size 1050186765

scripts/figures.qmd

@@ -287,31 +287,33 @@ ggplot(result, aes(year,Male/Female)) + geom_point() + geom_smooth(color="black"
 
 ```{r}
 #Stereotypes data preparation
-files = read.csv("~/Downloads/citations_by_article.csv",
-        col.names = c("filename","n_men","n_women","verbs_men",
-        "verbs_men_lemmatized","verbs_women","verbs_women_lemmatized"))
-z = duplicated(files$filename)
-files = files[!z,]
-library(stringr)
-files$filename = str_c(files$filename,".txt")
-z = duplicated(data$filename)
-verbs_data = data[!z,c("filename","sexe_prenom","year","rubrique")] %>% 
-  right_join(files,by="filename")
+#files = read.csv("~/Downloads/citations_by_article.csv",
+#        col.names = c("filename","n_men","n_women","verbs_men",
+#        "verbs_men_lemmatized","verbs_women","verbs_women_lemmatized"))
+#z = duplicated(files$filename)
+#files = files[!z,]
+#library(stringr)
+#files$filename = str_c(files$filename,".txt")
+#z = duplicated(data$filename)
+#verbs_data = data[!z,c("filename","sexe_prenom","year","rubrique")] %>% 
+#  right_join(files,by="filename")
 #verbs_data = filter(verbs_data,sexe_prenom =="Men")
 verbs = unique(read.csv("https://raw.githubusercontent.com/gillesbastin/old_fashion_nlp/refs/heads/main/cues_all.csv")$lemmatized_cue)
 ```
 
 ```{r}
 ##Compute odds ratios
+verbs = unique(read.csv("https://raw.githubusercontent.com/gillesbastin/old_fashion_nlp/refs/heads/main/cues_all.csv")$lemmatized_cue)
+
 threshold = 30
-men = verbs_data %>% group_by(year) %>% mutate(
+men = data %>% group_by(year) %>% mutate(
     verbs_men_lemmatized = strsplit(verbs_men_lemmatized, ";")) %>% 
     unnest(verbs_men_lemmatized) %>% 
     count(verbs_men_lemmatized) %>% ungroup() %>%
     complete(verbs_men_lemmatized = verbs,fill = list(n = 0,year = 1945)) %>%
     arrange(verbs_men_lemmatized)
-  
-men <- men %>%
+z = is.na(men$verbs_men_lemmatized)
+men <- men[!z,] %>%
   pivot_wider(
     names_from = verbs_men_lemmatized, 
     values_from = n, 
@@ -324,14 +326,14 @@ men = men %>% dplyr::select(-year) %>%
 
 
 
-women = verbs_data %>% group_by(year) %>% mutate(
+women = data %>% group_by(year) %>% mutate(
   verbs_women_lemmatized = strsplit(verbs_women_lemmatized, ";")) %>% 
   unnest(verbs_women_lemmatized) %>% 
   count(verbs_women_lemmatized) %>% ungroup() %>%
   complete(verbs_women_lemmatized = verbs,fill = list(n = 0,year = 1945)) %>%
   arrange(verbs_women_lemmatized)
-
-women <- women %>%
+z = is.na(men$verbs_men_lemmatized)
+women <- women[z,] %>%
   pivot_wider(
     names_from = verbs_women_lemmatized, 
     values_from = n,