|
|
|
@@ -61,53 +61,53 @@ Now we extract the words that were used with higher frequency by one party and c |
|
|
|
```{r} |
|
|
|
talks %>% |
|
|
|
left_join(speaker, by=c(speaker='id')) %>% |
|
|
|
group_by(fraktion) %>% |
|
|
|
summarize(full_text=str_c(content, collapse="\n")) -> talks_by_fraktion |
|
|
|
group_by(fraction) %>% |
|
|
|
summarize(full_text=str_c(content, collapse="\n")) -> talks_by_fraction |
|
|
|
``` |
|
|
|
For each party, we want to get a tibble of words with frequency. |
|
|
|
```{r} |
|
|
|
#AfD |
|
|
|
Worte <- str_extract_all(talks_by_fraktion$full_text[[1]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
Worte <- str_extract_all(talks_by_fraction$full_text[[1]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
afdtotal = length(Worte) |
|
|
|
tibble(Worte) %>% group_by(Worte) %>% count() %>% mutate(freq =n/afdtotal) -> afd_words |
|
|
|
|
|
|
|
#AfD&Fraktionslos |
|
|
|
Worte <- str_extract_all(talks_by_fraktion$full_text[[2]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
Worte <- str_extract_all(talks_by_fraction$full_text[[2]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
afdundfraktionslostotal = length(Worte) |
|
|
|
tibble(Worte) %>% group_by(Worte) %>% count() %>% mutate(freq =n/afdundfraktionslostotal) -> afdundfraktionslos_words |
|
|
|
|
|
|
|
#BÜNDNIS 90 / DIE GRÜNEN |
|
|
|
Worte <- str_extract_all(talks_by_fraktion$full_text[[3]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
Worte <- str_extract_all(talks_by_fraction$full_text[[3]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
grünetotal = length(Worte) |
|
|
|
tibble(Worte) %>% group_by(Worte) %>% count() %>% mutate(freq =n/grünetotal) -> grüne_words |
|
|
|
|
|
|
|
#CDU/CSU |
|
|
|
Worte <- str_extract_all(talks_by_fraktion$full_text[[4]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
Worte <- str_extract_all(talks_by_fraction$full_text[[4]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
cdutotal = length(Worte) |
|
|
|
tibble(Worte) %>% group_by(Worte) %>% count() %>% mutate(freq =n/cdutotal) -> cdu_words |
|
|
|
|
|
|
|
#DIE LINKE |
|
|
|
Worte <- str_extract_all(talks_by_fraktion$full_text[[5]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
Worte <- str_extract_all(talks_by_fraction$full_text[[5]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
linketotal = length(Worte) |
|
|
|
tibble(Worte) %>% group_by(Worte) %>% count() %>% mutate(freq =n/linketotal) -> linke_words |
|
|
|
|
|
|
|
#FDP |
|
|
|
Worte <- str_extract_all(talks_by_fraktion$full_text[[6]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
Worte <- str_extract_all(talks_by_fraction$full_text[[6]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
fdptotal = length(Worte) |
|
|
|
tibble(Worte) %>% group_by(Worte) %>% count() %>% mutate(freq =n/fdptotal) -> fdp_words |
|
|
|
|
|
|
|
#Fraktionslos |
|
|
|
Worte <- str_extract_all(talks_by_fraktion$full_text[[7]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
Worte <- str_extract_all(talks_by_fraction$full_text[[7]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
fraktionslostotal = length(Worte) |
|
|
|
tibble(Worte) %>% group_by(Worte) %>% count() %>% mutate(freq =n/fraktionslostotal) -> fraktionslos_words |
|
|
|
|
|
|
|
#SPD |
|
|
|
Worte <- str_extract_all(talks_by_fraktion$full_text[[8]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
Worte <- str_extract_all(talks_by_fraction$full_text[[8]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
spdtotal = length(Worte) |
|
|
|
tibble(Worte) %>% group_by(Worte) %>% count() %>% mutate(freq =n/spdtotal) -> spd_words |
|
|
|
|
|
|
|
#NA |
|
|
|
Worte <- str_extract_all(talks_by_fraktion$full_text[[9]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
Worte <- str_extract_all(talks_by_fraction$full_text[[9]], "\\b[a-zA-ZäöüÄÖÜß]+\\b")[[1]] |
|
|
|
natotal = length(Worte) |
|
|
|
tibble(Worte) %>% group_by(Worte) %>% count() %>% mutate(freq =n/natotal) -> na_words |
|
|
|
|
|
|
|
@@ -117,34 +117,34 @@ total <- sum(all_words$n) |
|
|
|
all_words %>% group_by(Worte) %>% summarize(n = sum(n), part= sum(n)/total) -> all_words |
|
|
|
``` |
|
|
|
|
|
|
|
Now we want to extract the words that are more frequently used by a specific `fraktion`. |
|
|
|
Now we want to extract the words that are more frequently used by a specific fraction. |
|
|
|
```{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, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
afd_words %>% transmute(freq, fraction_n = n) %>% left_join(all_words) %>% transmute(fraction_freq = freq, total_freq = part, fraction_n, total_n = n, rel_quotient = fraction_freq/total_freq, abs_quotient = fraction_n/total_n) %>% arrange(-abs_quotient, -fraction_n) %>% filter(rel_quotient > 1) -> afd_high_frequent |
|
|
|
select(afd_high_frequent, fraction_n, total_n, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
|
|
|
|
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, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
afdundfraktionslos_words %>% transmute(freq, fraction_n = n) %>% left_join(all_words) %>% transmute(fraction_freq = freq, total_freq = part, fraction_n, total_n = n, rel_quotient = fraction_freq/total_freq, abs_quotient = fraction_n/total_n) %>% arrange(-abs_quotient, -fraction_n) %>% filter(rel_quotient > 1) -> afdundfraktionslos_high_frequent |
|
|
|
select(afdundfraktionslos_high_frequent, fraction_n, total_n, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
|
|
|
|
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, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
grüne_words %>% transmute(freq, fraction_n = n) %>% left_join(all_words) %>% transmute(fraction_freq = freq, total_freq = part, fraction_n, total_n = n, rel_quotient = fraction_freq/total_freq, abs_quotient = fraction_n/total_n) %>% arrange(-abs_quotient, -fraction_n) %>% filter(rel_quotient > 1) -> grüne_high_frequent |
|
|
|
select(grüne_high_frequent, fraction_n, total_n, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
|
|
|
|
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, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
cdu_words %>% transmute(freq, fraction_n = n) %>% left_join(all_words) %>% transmute(fraction_freq = freq, total_freq = part, fraction_n, total_n = n, rel_quotient = fraction_freq/total_freq, abs_quotient = fraction_n/total_n) %>% arrange(-abs_quotient, -fraction_n) %>% filter(rel_quotient > 1) -> cdu_high_frequent |
|
|
|
select(cdu_high_frequent, fraction_n, total_n, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
|
|
|
|
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, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
linke_words %>% transmute(freq, fraction_n = n) %>% left_join(all_words) %>% transmute(fraction_freq = freq, total_freq = part, fraction_n, total_n = n, rel_quotient = fraction_freq/total_freq, abs_quotient = fraction_n/total_n) %>% arrange(-abs_quotient, -fraction_n) %>% filter(rel_quotient > 1) -> linke_high_frequent |
|
|
|
select(linke_high_frequent, fraction_n, total_n, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
|
|
|
|
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, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
fdp_words %>% transmute(freq, fraction_n = n) %>% left_join(all_words) %>% transmute(fraction_freq = freq, total_freq = part, fraction_n, total_n = n, rel_quotient = fraction_freq/total_freq, abs_quotient = fraction_n/total_n) %>% arrange(-abs_quotient, -fraction_n) %>% filter(rel_quotient > 1) -> fdp_high_frequent |
|
|
|
select(fdp_high_frequent, fraction_n, total_n, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
|
|
|
|
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, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
fraktionslos_words %>% transmute(freq, fraction_n = n) %>% left_join(all_words) %>% transmute(fraction_freq = freq, total_freq = part, fraction_n, total_n = n, rel_quotient = fraction_freq/total_freq, abs_quotient = fraction_n/total_n) %>% arrange(-abs_quotient, -fraction_n) %>% filter(rel_quotient > 1) -> fraktionslos_high_frequent |
|
|
|
select(fraktionslos_high_frequent, fraction_n, total_n, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
|
|
|
|
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, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
spd_words %>% transmute(freq, fraction_n = n) %>% left_join(all_words) %>% transmute(fraction_freq = freq, total_freq = part, fraction_n, total_n = n, rel_quotient = fraction_freq/total_freq, abs_quotient = fraction_n/total_n) %>% arrange(-abs_quotient, -fraction_n) %>% filter(rel_quotient > 1) -> spd_high_frequent |
|
|
|
select(spd_high_frequent, fraction_n, total_n, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
|
|
|
|
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, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
na_words %>% transmute(freq, fraction_n = n) %>% left_join(all_words) %>% transmute(fraction_freq = freq, total_freq = part, fraction_n, total_n = n, rel_quotient = fraction_freq/total_freq, abs_quotient = fraction_n/total_n) %>% arrange(-abs_quotient, -fraction_n) %>% filter(rel_quotient > 1) -> na_high_frequent |
|
|
|
select(na_high_frequent, fraction_n, total_n, abs_quotient, rel_quotient) %>% filter(total_n > 80) |
|
|
|
``` |
|
|
|
|
|
|
|
We compare these words with `hitlerwords`. |
|
|
|
@@ -161,7 +161,7 @@ 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&Fraktionslos", "BÜNDNIS 90 / DIE GRÜNEN", "CDU/CSU", "DIE LINKE", "FDP", "Fraktionslos", "SPD"), |
|
|
|
tibble(fraction = 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(percent = 100*absolute/total) -> hitler_comparison |
|
|
|
|
