Find Kanye

First we need to find the artist ID for Kanye. We can use search_artist() to look for him.

library(geniusr)  # access genius api
library(dplyr)  # manipulate data
library(knitr)  # pretty table printing

geniusr::search_artist("kanye west") %>% 
  knitr::kable()  # prints the table nice

Kanye’s ID on Genius is 72 as a solo artist. We can save this value as the object kanye_id and use it to get metadata about him. This includes the web address for his artist page on Genius, a link to the image of him used on the site and the number of people ‘following’ his lyrics page.

# artist ID
kanye_id <- 72

# access meta info
artist_meta <- geniusr::get_artist_meta(
  artist_id = kanye_id
)

# preview
dplyr::glimpse(artist_meta)

## Observations: 1
## Variables: 5
## $ artist_id        <int> 72
## $ artist_name      <chr> "Kanye West"
## $ artist_url       <chr> "https://genius.com/artists/Kanye-west"
## $ artist_image_url <chr> "https://images.genius.com/92fee84306e9a1ec88...
## $ followers_count  <int> 8754

Get songs

Now we can use Kanye’s artist ID to obtain all his songs on Genius.

# get all songs for a given artist id
kanye_songs <- geniusr::get_artist_songs(
  artist_id = kanye_id
)

# a random preview
dplyr::sample_n(kanye_songs, 10) %>%
  dplyr::select(song_name) %>% 
  knitr::kable()

We can also access a greater list of data for each song, including the album name and release date. We can use the map_df function from the purrr package to look for the meta data for each song in turn.

library(purrr)  # functional programming

# apply function over each song id
songs_meta <- purrr::map_df(
  kanye_songs$song_id,
  geniusr::get_song_meta
)

# a random preview
dplyr::sample_n(songs_meta, 10) %>% 
  dplyr::select(song_name, album_name) %>% 
  knitr::kable()

Looking at the album names, it seems we’ve got songs from 37 albums at least plus a bunch that are unknown or unclassified.

# the songs are from which albums?
unique(songs_meta$album_name)

##  [1] NA                                                                
##  [2] "Def Poetry Jam"                                                  
##  [3] "Kanye West's Visionary Streams of Consciousness"                 
##  [4] "Zane Lowe BBC Radio Interviews (Kanye West)"                     
##  [5] "The Life of Pablo"                                               
##  [6] "808s & Heartbreak"                                               
##  [7] "Late Registration"                                               
##  [8] "The College Dropout"                                             
##  [9] "Freshmen Adjustment"                                             
## [10] "World Record Holders"                                            
## [11] "ye"                                                              
## [12] "My Beautiful Dark Twisted Fantasy"                               
## [13] "VH1 Storytellers"                                                
## [14] "Get Well Soon..."                                                
## [15] "Freshmen Adjustment Vol. 2"                                      
## [16] "The Cons, Volume 5: Refuse to Die"                               
## [17] "Graduation"                                                      
## [18] "Can't Tell Me Nothing"                                           
## [19] "Kon the Louis Vuitton Don"                                       
## [20] "Yeezus"                                                          
## [21] "I'm Good"                                                        
## [22] "Graduation \"Bonus Tracks, Remixes, Unreleased\" EP"             
## [23] "Turbo Grafx 16*"                                                 
## [24] "G.O.O.D. Fridays"                                                
## [25] "Kanye West Presents Good Music Cruel Summer"                     
## [26] "Kanye's Poop-di-Scoopty 2018"                                    
## [27] "King"                                                            
## [28] "Freshmen Adjustment Vol. 3"                                      
## [29] "2016 G.O.O.D. Fridays"                                           
## [30] "Welcome to Kanye's Soul Mix Show"                                
## [31] "Late Orchestration"                                              
## [32] "College Dropout: Video Anthology"                                
## [33] "The Lost Tapes"                                                  
## [34] "NBA 2K13 Soundtrack"                                             
## [35] "Rapper's Delight"                                                
## [36] "Boys Don't Cry (Magazine)"                                       
## [37] "The Man With the Iron Fists (Original Motion Picture Soundtrack)"
## [38] "Coach Carter (Music from the Motion Picture)"

So you can see ye is definitely in the list of albums and we can filter our data frame so we just get the seven tracks from that particular album. Maybe we’ll explore the other lyrics more deeply another day.

# filter songs from album 'ye'
ye <- songs_meta %>% 
  dplyr::filter(album_name == "ye")

# preview songs
dplyr::select(ye, song_name)

## # A tibble: 7 x 1
##   song_name                  
##   <chr>                      
## 1 All Mine                   
## 2 Ghost Town                 
## 3 I Thought About Killing You
## 4 No Mistakes                
## 5 Violent Crimes             
## 6 Wouldn't Leave             
## 7 Yikes

We can fecth the lyrics from Genius for each song now that we have their details. We can do this using map_df() again to apply the scrape_lyrics_url() function to each row of our dataframe, where each row represents a single song.

# get lyrics
ye_lyrics <- purrr::map_df(
  ye$song_lyrics_url,
  geniusr::scrape_lyrics_url
)

# join additional information
ye_lyrics <- ye_lyrics %>%
  dplyr::group_by(song_name) %>% 
  dplyr::mutate(line_number = row_number()) %>% 
  dplyr::ungroup() %>% 
  dplyr::left_join(ye, by = "song_name")

# check out a sample of lines
ye_lyrics %>% 
  dplyr::sample_n(10) %>% 
  dplyr::select(line, song_name) %>% 
  knitr::kable()

Words

library(tidytext)  # wrangle text

ye_words <- ye_lyrics %>%
  tidytext::unnest_tokens(word, line) %>%  # separate the tokens out
  dplyr::anti_join(tidytext::stop_words)  # remove words like 'if', 'and', 'but'

dplyr::sample_n(ye_words, 10) %>% 
  dplyr::select(word, song_name) %>% 
  knitr::kable()

library(DT)  # interactive tables

ye_words %>%
  dplyr::count(word, sort = TRUE) %>% 
  DT::datatable(
    options = list(
      autoWidth = TRUE,
      pageLength = 10
    )
  )

#devtools::install_github("matt-dray/dray")
library(dray)  # for ye_cols
dray::ye_cols  # see the named colours

## mountain_blue    grass_blue   cloud_blue1   cloud_white    cloud_grey 
##     "#233956"     "#0e1e27"     "#7a8aa2"     "#dfd7c9"     "#b5b2b0" 
##   cloud_blue2    text_green 
##     "#9da3ae"     "#31ef56"

library(ggplot2)  # plots

ye_words %>%
  dplyr::count(word, sort = TRUE) %>%  # tally words
  dplyr::filter(n > 5) %>%  # more than5 occurrences 
  dplyr::mutate(word = reorder(word, n)) %>%  # order by count
  ggplot2::ggplot(aes(word, n)) +
  geom_col(fill = ye_cols["mountain_blue"]) +
  labs(
    title = "Frequency of words in 'ye' (2018) by Kanye West",
    subtitle = "Using the geniusr and tidytext packages",
    x = "", y = "Count",
    caption = "Lyrics from genius.com"
  ) +
  coord_flip() +
  theme(  # apply ye theming
    plot.title = element_text(colour = ye_cols["cloud_white"]),
    plot.subtitle = element_text(colour = ye_cols["cloud_white"]),
    plot.caption = element_text(colour = ye_cols["cloud_blue1"]),
    axis.title = element_text(colour = ye_cols["text_green"]),
    axis.text = element_text(colour = ye_cols["text_green"]),
    plot.background = element_rect(fill = ye_cols["grass_blue"]),
    panel.background = element_rect(fill = ye_cols["cloud_grey"]),
    panel.grid = element_line(ye_cols["cloud_grey"])
  )

Bigrams

ye_bigrams <- ye_lyrics %>%
  tidytext::unnest_tokens(
    bigram,
    line,
    token = "ngrams",
    n = 2
  )

library(tidyr)  # to isolate bigram words

ye_bigrams_separated <- ye_bigrams %>%
  tidyr::separate(
    bigram,
    c("word1", "word2"),
    sep = " "
  )

ye_bigrams_filtered <- ye_bigrams_separated %>%
  dplyr::filter(
    !word1 %in% tidytext::stop_words$word,
    !word2 %in% tidytext::stop_words$word
  ) %>%
  dplyr::mutate(bigram = paste(word1, word2))

sample_n(ye_bigrams_filtered, 10) %>% 
  dplyr::select(bigram, song_name)

## # A tibble: 10 x 2
##    bigram              song_name                  
##    <chr>               <chr>                      
##  1 bleed yeah          Ghost Town                 
##  2 fallin dreamin      Violent Crimes             
##  3 premeditated murder I Thought About Killing You
##  4 gonna leave         All Mine                   
##  5 shit halfway        I Thought About Killing You
##  6 til niggas          Violent Crimes             
##  7 shit nigga          Yikes                      
##  8 supermodel thick    All Mine                   
##  9 mhm mhm             I Thought About Killing You
## 10 ayy i'ma            All Mine

ye_bigrams_filtered %>%
  dplyr::mutate(bigram = as.factor(bigram)) %>% 
  dplyr::count(bigram, sort = TRUE) %>% 
  DT::datatable(
    options = list(
      autoWidth = TRUE,
      pageLength = 10
    )
  )

ye_bigrams_filtered %>%
  dplyr::count(bigram, sort = TRUE) %>%
  dplyr::filter(n > 3) %>%
  dplyr::mutate(bigram = reorder(bigram, n)) %>%
  ggplot2::ggplot(aes(bigram, n)) +
  geom_col(fill = ye_cols["mountain_blue"]) +
  labs(
    title = "Frequency of bigrams in 'ye' (2018) by Kanye West",
    subtitle = "Using the geniusr and tidytext packages",
    x = "", y = "Count",
    caption = "Lyrics from genius.com"
  ) +
  coord_flip() +
  theme(  # apply ye theming
    plot.title = element_text(colour = ye_cols["cloud_white"]),
    plot.subtitle = element_text(colour = ye_cols["cloud_white"]),
    plot.caption = element_text(colour = ye_cols["cloud_blue1"]),
    axis.title = element_text(colour = ye_cols["text_green"]),
    axis.text = element_text(colour = ye_cols["text_green"]),
    plot.background = element_rect(fill = ye_cols["grass_blue"]),
    panel.background = element_rect(fill = ye_cols["cloud_grey"]),
    panel.grid = element_line(ye_cols["cloud_grey"])
  )

What did we learn?

It’s difficult to get a deep insight from looking at individual words from a 24-minute, seven-song album. You might argue that looking for deep insight from Kanye West’s lyrics is a fool’s errand anyway.

Despite this, ‘love’ and ‘feel’ were in the top 10, which might indicate Kanye expressing his feelings. ‘Bad’, ‘mistake’ and ‘pray’ were also repeated a bunch of times, which might also indicate what’s on Ye’s mind.

Most of the other most common words should probably have been removed as stop words but weren’t in our stop-word dictionary (e.g. ‘yeah’, ‘mhm’, ‘i’ma’, ‘gon’, ‘ayy’, ‘wanna’). Perhaps unsurprisingly, the flexibility of ‘shit’ and ‘fuck’ means they’re pretty high up the list.

We’ve seen how simple it is to use the geniusr functions search_artist(), get_artist_meta(), get_artist_songs(), get_songs_meta() and scrape_lyrics_url() in conjunction with purrr, followed by some tidytext.

The next step might be to look at Ye’s entire back catalogue and see how his lyrics have changed over time and how they compare to ye in particular.

Obviously I only made this post for the ‘tid-ye-text’ pun, so take it or leave it.