get_accounts.RdGet lists of Russian or Chinese Diplomats
get_accounts(country, group = c("diplomats"))currently supports "RU" and "CN" (or both: c("RU","CN"))
currently supports "diplomats"
returns data.frame with twitter handles and details on dipomats
tbc
tbc
options(tidyverse.quiet = TRUE)
library(tidyverse)
#> Warning: replacing previous import 'lifecycle::last_warnings' by 'rlang::last_warnings' when loading 'hms'
ru_accs <-
get_accounts(country = "RU",group = "diplomats")
#> Warning: Missing column names filled in: 'X10' [10], 'X11' [11], 'X12' [12], 'X13' [13]
#>
#> -- Column specification --------------------------------------------------------
#> cols(
#> country = col_character(),
#> ISO2 = col_character(),
#> cat = col_character(),
#> twitter_handle = col_character(),
#> remarks = col_character(),
#> user_id = col_logical(),
#> started_post = col_character(),
#> ended_post = col_character(),
#> last_checked = col_logical(),
#> X10 = col_logical(),
#> X11 = col_character(),
#> X12 = col_character(),
#> X13 = col_character()
#> )
#>
#> -- Column specification --------------------------------------------------------
#> cols(
#> handle = col_character(),
#> url_handle = col_character(),
#> gov_label = col_character(),
#> name = col_character(),
#> description = col_character(),
#> followers = col_character(),
#> verified = col_logical(),
#> date_scraped = col_date(format = ""),
#> filename = col_character(),
#> followers_num = col_double()
#> )
#>
#> -- Column specification --------------------------------------------------------
#> cols(
#> .default = col_character(),
#> user_id = col_double(),
#> protected = col_logical(),
#> followers_count = col_double(),
#> friends_count = col_double(),
#> listed_count = col_double(),
#> statuses_count = col_double(),
#> favourites_count = col_double(),
#> account_created_at = col_datetime(format = ""),
#> verified = col_logical(),
#> account_lang = col_logical(),
#> date_scraped = col_date(format = "")
#> )
#> i Use `spec()` for the full column specifications.
#> [1] "321 Russian diplomats and government accounts. Twitter transparency labels as of 2022-04-26. Account data as of 2022-04-26."
head(ru_accs,10)
#> # A tibble: 10 x 27
#> country ISO2 cat twitter_handle gov_label user_id screen_name name
#> <chr> <chr> <chr> <chr> <chr> <dbl> <chr> <chr>
#> 1 Afghanistan AF E RusEmbassyKabul Russia g~ 3.41e 8 RusEmbassy~ "Russi~
#> 2 Afghanistan AF C ruscg_mzs NA 7.95e17 RusCG_MZS "Russi~
#> 3 Albania AL E RussianAlbania Russia g~ 1.37e18 RussianAlb~ "Russi~
#> 4 Algeria DZ E AmbRus_Algerie NA 3.43e 8 AmbRus_Alg~ "Ambas~
#> 5 Angola AO E russembangola4 Rússia o~ 1.43e18 russembang~ "russe~
#> 6 Argentina AR E EmbRusiaEnArgEs NA 3.40e 8 EmbRusiaEn~ "Embaj~
#> 7 Argentina AR E EmbRusiaEnArgRu NA 2.84e 9 EmbRusiaEn~ "<U+041F><U+043E><U+0441><U+043E><U+043B>~
#> 8 Armenia AM E rusembassyARM NA 1.65e 9 rusembassy~ "<U+041F><U+043E><U+0441><U+043E><U+043B>~
#> 9 Armena AM C GyumriRussia NA 1.02e18 GyumriRuss~ "<U+0413><U+0435><U+043D><U+0435><U+0440>~
#> 10 Australia AU E RusEmbAU Russia g~ 2.39e 9 RusEmbAU "Russi~
#> # ... with 19 more variables: location <chr>, description <chr>, url <chr>,
#> # protected <lgl>, followers_count <dbl>, friends_count <dbl>,
#> # listed_count <dbl>, statuses_count <dbl>, favourites_count <dbl>,
#> # account_created_at <dttm>, verified <lgl>, profile_url <chr>,
#> # profile_expanded_url <chr>, account_lang <lgl>, profile_banner_url <chr>,
#> # profile_background_url <chr>, profile_image_url <chr>, data_scraped <date>,
#> # labels_scraped <date>
ru_accs %>%
group_by(cat) %>%
mutate(n_cat = n()) %>%
group_by(cat,n_cat,gov_label = gov_label != "") %>%
summarise(n = n()) %>%
mutate(perc = n/n_cat) %>% filter(gov_label == T)
#> `summarise()` has grouped output by 'cat', 'n_cat'. You can override using the `.groups` argument.
#> # A tibble: 6 x 5
#> # Groups: cat, n_cat [6]
#> cat n_cat gov_label n perc
#> <chr> <int> <lgl> <int> <dbl>
#> 1 A 7 TRUE 1 0.143
#> 2 C 66 TRUE 5 0.0758
#> 3 E 161 TRUE 88 0.547
#> 4 G 55 TRUE 14 0.255
#> 5 QG 11 TRUE 1 0.0909
#> 6 S 8 TRUE 3 0.375