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add 10 most used specific words of fraktionen

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JosuaKugler
2021-08-02 22:36:30 +02:00
parent ef29269d45
commit 0a97674b51
1 changed files with 18 additions and 30 deletions
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vignettes/hitlercomparison.Rmd
+18 -30
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@@ -1,5 +1,5 @@
---
title: "funwithdata"
title: "Analysis of vocabulary"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{funwithdata}
@@ -63,7 +63,6 @@ talks %>%
left_join(redner, by=c(redner='id')) %>%
group_by(fraktion) %>%
summarize(full_text=str_c(content, collapse="\n")) -> talks_by_fraktion
talks_by_fraktion
```
For each party, we want to get a tibble of words with frequency.
```{r}
@@ -121,23 +120,31 @@ all_words %>% group_by(Worte) %>% summarize(n = sum(n), part= sum(n)/total) -> a
Now we want to extract the words that are more frequently used by a specific `fraktion`.
```{r}
afd_words %>% transmute(freq, fraktion_n = n) %>% left_join(all_words) %>% transmute(fraktion_freq = freq, total_freq = part, fraktion_n, total_n = n, rel_quotient = fraktion_freq/total_freq, abs_quotient = fraktion_n/total_n) %>% arrange(-abs_quotient, -fraktion_n) %>% filter(rel_quotient > 1) -> afd_high_frequent
select(afd_high_frequent, fraktion_n, total_n)
afdundfraktionslos_words %>% transmute(freq, fraktion_n = n) %>% left_join(all_words) %>% transmute(fraktion_freq = freq, total_freq = part, fraktion_n, total_n = n, rel_quotient = fraktion_freq/total_freq, abs_quotient = fraktion_n/total_n) %>% arrange(-abs_quotient, -fraktion_n) %>% filter(rel_quotient > 1) -> afdundfraktionslos_high_frequent
select(afdundfraktionslos_high_frequent, fraktion_n, total_n)
grüne_words %>% transmute(freq, fraktion_n = n) %>% left_join(all_words) %>% transmute(fraktion_freq = freq, total_freq = part, fraktion_n, total_n = n, rel_quotient = fraktion_freq/total_freq, abs_quotient = fraktion_n/total_n) %>% arrange(-abs_quotient, -fraktion_n) %>% filter(rel_quotient > 1) -> grüne_high_frequent
select(grüne_high_frequent, fraktion_n, total_n)
cdu_words %>% transmute(freq, fraktion_n = n) %>% left_join(all_words) %>% transmute(fraktion_freq = freq, total_freq = part, fraktion_n, total_n = n, rel_quotient = fraktion_freq/total_freq, abs_quotient = fraktion_n/total_n) %>% arrange(-abs_quotient, -fraktion_n) %>% filter(rel_quotient > 1) -> cdu_high_frequent
select(cdu_high_frequent, fraktion_n, total_n)
linke_words %>% transmute(freq, fraktion_n = n) %>% left_join(all_words) %>% transmute(fraktion_freq = freq, total_freq = part, fraktion_n, total_n = n, rel_quotient = fraktion_freq/total_freq, abs_quotient = fraktion_n/total_n) %>% arrange(-abs_quotient, -fraktion_n) %>% filter(rel_quotient > 1) -> linke_high_frequent
select(linke_high_frequent, fraktion_n, total_n)
fdp_words %>% transmute(freq, fraktion_n = n) %>% left_join(all_words) %>% transmute(fraktion_freq = freq, total_freq = part, fraktion_n, total_n = n, rel_quotient = fraktion_freq/total_freq, abs_quotient = fraktion_n/total_n) %>% arrange(-abs_quotient, -fraktion_n) %>% filter(rel_quotient > 1) -> fdp_high_frequent
select(fdp_high_frequent, fraktion_n, total_n)
fraktionslos_words %>% transmute(freq, fraktion_n = n) %>% left_join(all_words) %>% transmute(fraktion_freq = freq, total_freq = part, fraktion_n, total_n = n, rel_quotient = fraktion_freq/total_freq, abs_quotient = fraktion_n/total_n) %>% arrange(-abs_quotient, -fraktion_n) %>% filter(rel_quotient > 1) -> fraktionslos_high_frequent
select(fraktionslos_high_frequent, fraktion_n, total_n)
spd_words %>% transmute(freq, fraktion_n = n) %>% left_join(all_words) %>% transmute(fraktion_freq = freq, total_freq = part, fraktion_n, total_n = n, rel_quotient = fraktion_freq/total_freq, abs_quotient = fraktion_n/total_n) %>% arrange(-abs_quotient, -fraktion_n) %>% filter(rel_quotient > 1) -> spd_high_frequent
select(spd_high_frequent, fraktion_n, total_n)
na_words %>% transmute(freq, fraktion_n = n) %>% left_join(all_words) %>% transmute(fraktion_freq = freq, total_freq = part, fraktion_n, total_n = n, rel_quotient = fraktion_freq/total_freq, abs_quotient = fraktion_n/total_n) %>% arrange(-abs_quotient, -fraktion_n) %>% filter(rel_quotient > 1) -> na_high_frequent
select(na_high_frequent, fraktion_n, total_n)
```
We compare these words with `hitlerwords`.
@@ -154,32 +161,13 @@ spd_high_frequent %>% mutate(Worte = str_to_lower(Worte)) %>% inner_join(hitlerw
na_high_frequent %>% mutate(Worte = str_to_lower(Worte)) %>% inner_join(hitlerwords) -> na_hitler_comparison
#not unique
tibble(fraktion = c("AfD", "AfD und Fraktionslose", "Grüne", "CDU", "Linke", "FDP", "Fraktionslos", "SPD", "NA"),
absolute = c(nrow(afd_hitler_comparison), nrow(afdundfraktionslos_hitler_comparison), nrow(grüne_hitler_comparison), nrow(cdu_hitler_comparison), nrow(linke_hitler_comparison), nrow(fdp_hitler_comparison), nrow(fraktionslos_hitler_comparison), nrow(spd_hitler_comparison), nrow(na_hitler_comparison)),
total = c(nrow(afd_words), nrow(afdundfraktionslos_words), nrow(grüne_words), nrow(cdu_words), nrow(linke_words), nrow(fdp_words), nrow(fraktionslos_words), nrow(spd_words), nrow(na_words))
) %>% mutate(relative = absolute/total) -> hitler_compare
tibble(fraktion = c("AfD", "AfD&Fraktionslos", "BÜNDNIS 90 / DIE GRÜNEN", "CDU/CSU", "DIE LINKE", "FDP", "Fraktionslos", "SPD"),
absolute = c(nrow(afd_hitler_comparison), nrow(afdundfraktionslos_hitler_comparison), nrow(grüne_hitler_comparison), nrow(cdu_hitler_comparison), nrow(linke_hitler_comparison), nrow(fdp_hitler_comparison), nrow(fraktionslos_hitler_comparison), nrow(spd_hitler_comparison)),
total = c(nrow(afd_words), nrow(afdundfraktionslos_words), nrow(grüne_words), nrow(cdu_words), nrow(linke_words), nrow(fdp_words), nrow(fraktionslos_words), nrow(spd_words))
) %>% mutate(n = absolute/total) -> hitler_comparison
hitler_comparison
```
Dead code:
```r
1000*nrow(afd_hitler_comparison) / nrow(afd_words)
1000*nrow(afdundfraktionslos_hitler_comparison) / nrow(afdundfraktionslos_words)
1000*nrow(grüne_hitler_comparison) / nrow(grüne_words)
1000*nrow(cdu_hitler_comparison) / nrow(cdu_words)
1000*nrow(linke_hitler_comparison) / nrow(linke_words)
1000*nrow(fdp_hitler_comparison) / nrow(fdp_words)
1000*nrow(fraktionslos_hitler_comparison) / nrow(fraktionslos_words)
1000*nrow(spd_hitler_comparison) / nrow(spd_words)
1000*nrow(na_hitler_comparison) / nrow(na_words)
1000*sum(afd_hitler_comparison$fraktion_n) / afdtotal
1000*sum(afdundfraktionslos_hitler_comparison$fraktion_n) / afdundfraktionslostotal
1000*sum(grüne_hitler_comparison$fraktion_n) / grünetotal
1000*sum(cdu_hitler_comparison$fraktion_n) / cdutotal
1000*sum(linke_hitler_comparison$fraktion_n) / linketotal
1000*sum(fdp_hitler_comparison$fraktion_n) / fdptotal
1000*sum(fraktionslos_hitler_comparison$fraktion_n) / fraktionslostotal
1000*sum(spd_hitler_comparison$fraktion_n) / spdtotal
1000*sum(na_hitler_comparison$fraktion_n) / natotal
Finally, we want to plot our results:
```{r, fig.width=7}
bar_plot_fraktionen(hitler_comparison)
```