MEA 4600 Passion Project -Beyonce
Devon Margulies
05/09/2022
This report is an exploration of growth for the artist Beyonce.
Warning: Explicit Content
Beyoncé Giselle Knowles-Carter is an American singer, songwriter, and actress who was born in Houston, Texas on September 4th, 1981. Beyoncé rose to fame in the late 1990s as the main vocalist of Destiny’s Child, one of the best-selling girl groups of the time. She is now one of the most globally well-known artists, and in 2014, she was awarded Forbes’ Most Powerful Celebrity.
I will be looking at how/if Beyoncé’s music is effected by events that occur in her life. I will be looking at her six main albums “Dangerously in Love (2003),”B’Day” (2006), “I AM… SASHA FIERCE” (2008), “4” (2011), “BEYONCÉ” (2014) and “Lemonade” (2016). I chose only to look at these works with the help of Wikipedia and Spotify. Spotify also recognizes “B’Day Deluxe Edition” (2007), “Above and Beyoncé Dance Mixes” (2009), “I Am…World Tour” (2010), “HOMECOMING: THE LIVE ALBUM” (2019), “The Lion King: The Gift” (2019), and “The Lion King: The Gift [Deluxe Edition]” (2020). I will look at the text within each of Beyonce’s albums to look at overall tone and sentiment. I will be looking at if the sentiment of the albums change and if there was any major life events going on at the time to cause this change. I will also be looking the chords, valence (joyfulness), and dancability of the albums to look for changes. I will be using both a lyrical data set from https://www.kaggle.com/datasets/deepshah16/song-lyrics-dataset, which was edited down in excel and then uploaded to R, and Spotify API to get my necessary information.
First I download the necessary packages
library("tidytext")
library("wordcloud2")
library("tidyverse")## Warning: package 'tidyr' was built under R version 4.0.5## Warning: package 'readr' was built under R version 4.0.5library("tidyr")
library("readr")
library("rjson")## Warning: package 'rjson' was built under R version 4.0.5library(devtools)
devtools::install_github('charlie86/spotifyr')
devtools::install_github("lchiffon/wordcloud2")
library(spotifyr)
library(tidyverse)
library(knitr)
library(ggjoy)
library(ggridges)
library(dplyr)
library(plotly)
library(ggplot2)
library(ggthemes)
library(textdata)
library(jsonlite)## Warning: package 'jsonlite' was built under R version 4.0.5library(readxl)
library(fastmap)Next I use my Spoitfy API access keys to download Beyonce Spotify data
Here I am going to download each individual album
“Dangerously In Love”
Dangerously In Love is the debut studio album by American singer Beyoncé. Columbia Records and Music World Entertainment released it on June 20, 2003. This album was released after Destiny’s Child revealed that they will make individual albums during the recording of their third studio album, Survivor.
Beyonce_DIL <- read_excel("~/Desktop/MEA_4600/Passion_Project/Beyonce_DIL.xlsx")
View(Beyonce_DIL)How many words are in this album
Beyonce_DIL %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
count()## # A tibble: 1 × 1
## n
## <int>
## 1 84708470
How many times do the most popular words occur within the album?
Beyonce_DIL %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
head(10) %>%
knitr::kable()| word | n |
|---|---|
| love | 136 |
| baby | 94 |
| beyonc | 52 |
| boy | 51 |
| huh | 49 |
| time | 48 |
| crazy | 44 |
| girl | 40 |
| gonna | 37 |
| feel | 35 |
What is the sentiment of these words?
Beyonce_DIL %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
inner_join(get_sentiments("bing")) %>%
inner_join(get_sentiments("afinn")) %>%
head(10) %>%
knitr::kable()| word | n | sentiment | value |
|---|---|---|---|
| love | 136 | positive | 3 |
| crazy | 44 | negative | -2 |
| loving | 17 | positive | 2 |
| cancer | 10 | negative | -1 |
| damn | 7 | negative | -4 |
| sexy | 7 | positive | 3 |
| cry | 6 | negative | -1 |
| free | 6 | positive | 1 |
| hurt | 6 | negative | -2 |
| cool | 5 | positive | 1 |
note –> interesting “crazy” is negative when in context it is supposed to be “crazy love” or “crazy in love”
What words stand out the most in a word cloud
Beyonce_DIL %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
wordcloud2()“love”, “baby”, “crazy”
Looking at Spotify Data
Beyonce_Spotify %>%
filter(album_name %in% "Dangerously In Love") -> DILAlbum
View(DILAlbum)Which track in Dangerously In Love has the highest danceability?
Beyonce_Spotify %>%
filter(album_name %in% "Dangerously In Love") %>%
select(danceability, album_name, track_name) %>%
kable()| danceability | album_name | track_name |
|---|---|---|
| 0.646 | Dangerously In Love | Crazy In Love (feat. Jay-Z) |
| 0.588 | Dangerously In Love | Naughty Girl |
| 0.655 | Dangerously In Love | Baby Boy (feat. Sean Paul) |
| 0.736 | Dangerously In Love | Hip Hop Star (feat. Big Boi & Sleepy Brown) |
| 0.711 | Dangerously In Love | Be With You |
| 0.750 | Dangerously In Love | Me, Myself and I |
| 0.662 | Dangerously In Love | Yes |
| 0.447 | Dangerously In Love | Signs (feat. Missy Elliott) |
| 0.568 | Dangerously In Love | Speechless |
| 0.493 | Dangerously In Love | That’s How You Like It (feat. Jay-Z) |
| 0.652 | Dangerously In Love | The Closer I Get to You (feat. Beyoncé Knowles) |
| 0.609 | Dangerously In Love | Dangerously In Love |
| 0.650 | Dangerously In Love | Beyoncé Interlude |
| 0.388 | Dangerously In Love | Gift from Virgo |
| 0.469 | Dangerously In Love | Daddy |
| 0.664 | Dangerously In Love | Crazy In Love (feat. Jay-Z) |
| 0.735 | Dangerously In Love | Naughty Girl |
| 0.689 | Dangerously In Love | Baby Boy (feat. Sean Paul) |
| 0.741 | Dangerously In Love | Hip Hop Star (feat. Big Boi & Sleepy Brown) |
| 0.710 | Dangerously In Love | Be With You |
| 0.747 | Dangerously In Love | Me, Myself and I |
| 0.638 | Dangerously In Love | Yes |
| 0.373 | Dangerously In Love | Signs (feat. Missy Elliott) |
| 0.542 | Dangerously In Love | Speechless |
| 0.435 | Dangerously In Love | That’s How You Like It (feat. Jay-Z) |
| 0.630 | Dangerously In Love | The Closer I Get to You (feat. Beyoncé Knowles) |
| 0.619 | Dangerously In Love | Dangerously In Love |
| 0.693 | Dangerously In Love | Beyoncé Interlude |
| 0.349 | Dangerously In Love | Gift from Virgo |
| 0.683 | Dangerously In Love | Work It Out |
| 0.618 | Dangerously In Love | ’03 Bonnie & Clyde (feat. Beyoncé) |
“Me, Myself and I” has the highest dancability with .747
Can each track’s danceability be shown in a graph?
DILAlbum %>%
ggplot()+
geom_col(aes(x=track_name, y=danceability))+
theme_economist()+
theme(axis.text.x = element_text(angle = 90))
What is the distribution of the danceability within Dangerously In Love?
ggplot(DILAlbum, aes(x=danceability)) +
geom_density(alpha=0.7)+
labs(x="Danceability", y="Density") +
theme_economist()+
ggtitle("Distribution of Danceability Data in Dangerously In Love")
Using a heatmap code created by http://student.elon.edu/bwilliamson5/FinalProject/index.html to analyze danceability in Dangerously in Love
ggplot(data = DILAlbum, aes(x = danceability, y = track_name)) +
geom_tile(aes(fill=danceability, height=1 , width=.1),colour="red") +
scale_y_discrete(breaks = DILAlbum$track_name) +
scale_fill_gradient2(low = "#FF0000", midpoint=0.6,
space="Lab", mid="#FFE500", high = "#09B505") +
labs(x = "Danceability") +
labs(y = "Track Name") +
labs(title = "Dangerously In Love Album Danceability")
“B’Day”
B’Day is Beyoncé’s second studio album. Columbia Records, Music World Entertainment, and Sony Urban Music published it on September 4, 2006, to coincide with her twenty-fifth birthday in several countries, and a day later in the United States.
Beyonce_BDay <- read_excel("~/Desktop/MEA_4600/Passion_Project/Beyonce_BDay.xlsx")
View(Beyonce_BDay)How many words are in this album
Beyonce_BDay %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
count()## # A tibble: 1 × 1
## n
## <int>
## 1 62866286
How many times do the most popular words occur within the album
Beyonce_BDay %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
head(10) %>%
knitr::kable()| word | n |
|---|---|
| mama | 52 |
| hey | 39 |
| body | 37 |
| upgrade | 33 |
| baby | 30 |
| bodied | 30 |
| time | 27 |
| dress | 26 |
| freakum | 25 |
| light | 25 |
What is the sentiment of these words?
Beyonce_BDay %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
inner_join(get_sentiments("bing")) %>%
inner_join(get_sentiments("afinn")) %>%
head(10) %>%
knitr::kable()| word | n | sentiment | value |
|---|---|---|---|
| lied | 15 | negative | -2 |
| damned | 12 | negative | -4 |
| alarm | 5 | negative | -2 |
| hurt | 5 | negative | -2 |
| easy | 4 | positive | 1 |
| hard | 4 | negative | -1 |
| hate | 4 | negative | -3 |
| love | 4 | positive | 3 |
| pretend | 4 | negative | -1 |
| impress | 3 | positive | 3 |
Majority have negative sentiment but these are without the soft & stop words.
What words stand out the most in a word cloud?
Beyonce_BDay %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
wordcloud2()“hey,”baby”, “mama”
Loading Spotify Data
Beyonce_Spotify %>%
filter(album_name %in% "B'Day") -> BDayAlbum
View(BDayAlbum)Which track in B’Day has the highest danceability?
Beyonce_Spotify %>%
filter(album_name %in% "B'Day") %>%
select(danceability, album_name, track_name) %>%
kable()| danceability | album_name | track_name |
|---|---|---|
| 0.763 | B’Day | Deja Vu (feat. Jay-Z) |
| 0.865 | B’Day | Get Me Bodied |
| 0.682 | B’Day | Suga Mama |
| 0.474 | B’Day | Upgrade U (feat. Jay-Z) |
| 0.456 | B’Day | Ring The Alarm |
| 0.810 | B’Day | Kitty Kat |
| 0.683 | B’Day | Freakum Dress |
| 0.796 | B’Day | Green Light |
| 0.576 | B’Day | Irreplaceable |
| 0.378 | B’Day | Resentment |
| 0.706 | B’Day | Encore For The Fans |
| 0.483 | B’Day | Listen (From the Motion Picture “Dreamgirls”) |
| 0.911 | B’Day | Get Me Bodied - Extended Mix |
| 0.763 | B’Day | Deja Vu (feat. Jay-Z) |
| 0.865 | B’Day | Get Me Bodied |
| 0.682 | B’Day | Suga Mama |
| 0.474 | B’Day | Upgrade U (feat. Jay-Z) |
| 0.456 | B’Day | Ring The Alarm |
| 0.810 | B’Day | Kitty Kat |
| 0.683 | B’Day | Freakum Dress |
| 0.796 | B’Day | Green Light |
| 0.576 | B’Day | Irreplaceable |
| 0.378 | B’Day | Resentment |
| 0.706 | B’Day | Encore For The Fans |
| 0.483 | B’Day | Listen (From the Motion Picture “Dreamgirls”) |
| 0.911 | B’Day | Get Me Bodied - Extended Mix |
| 0.763 | B’Day | Deja Vu (feat. Jay-Z) |
| 0.865 | B’Day | Get Me Bodied |
| 0.682 | B’Day | Suga Mama |
| 0.474 | B’Day | Upgrade U (feat. Jay-Z) |
| 0.456 | B’Day | Ring The Alarm |
| 0.810 | B’Day | Kitty Kat |
| 0.683 | B’Day | Freakum Dress |
| 0.796 | B’Day | Green Light |
| 0.576 | B’Day | Irreplaceable |
| 0.378 | B’Day | Resentment |
| 0.705 | B’Day | Check On It (feat. Bun B & Slim Thug) |
| 0.761 | B’Day | Deja Vu (feat. Jay-Z) |
| 0.864 | B’Day | Get Me Bodied |
| 0.714 | B’Day | Suga Mama |
| 0.676 | B’Day | Upgrade U (feat. Jay-Z) |
| 0.457 | B’Day | Ring The Alarm |
| 0.819 | B’Day | Kitty Kat |
| 0.689 | B’Day | Freakum Dress |
| 0.795 | B’Day | Green Light |
| 0.453 | B’Day | Irreplaceable |
| 0.440 | B’Day | Resentment |
| 0.702 | B’Day | Check On It (feat. Bun B & Slim Thug) |
| 0.634 | B’Day | Deja Vu (feat. Jay-Z) - The Remix |
| 0.722 | B’Day | Encore For The Fans |
| 0.456 | B’Day | Listen (From the Motion Picture “Dreamgirls”) |
| 0.908 | B’Day | Get Me Bodied - Extended Mix |
| 0.763 | B’Day | Deja Vu (feat. Jay-Z) |
| 0.865 | B’Day | Get Me Bodied |
| 0.682 | B’Day | Suga Mama |
| 0.474 | B’Day | Upgrade U (feat. Jay-Z) |
| 0.456 | B’Day | Ring The Alarm |
| 0.810 | B’Day | Kitty Kat |
| 0.683 | B’Day | Freakum Dress |
| 0.796 | B’Day | Green Light |
| 0.576 | B’Day | Irreplaceable |
| 0.378 | B’Day | Resentment |
| 0.705 | B’Day | Check On It (feat. Bun B & Slim Thug) |
“Get Me Bodied” has the highest dancability with .865
Each track’s danceability shown in a graph
BDayAlbum %>%
ggplot()+
geom_col(aes(x=track_name, y=danceability))+
theme_economist()+
theme(axis.text.x = element_text(angle = 90))
What is the distribution of the danceability within B’Day?
ggplot(BDayAlbum, aes(x=danceability)) +
geom_density(alpha=0.7)+
labs(x="Danceability", y="Density") +
theme_economist()+
ggtitle("Distribution of Danceability Data in B'Day")
Using a heatmap code created by http://student.elon.edu/bwilliamson5/FinalProject/index.html to analyze danceability in B’Day
ggplot(data = BDayAlbum, aes(x = danceability, y = track_name)) +
geom_tile(aes(fill=danceability, height=1 , width=.1),colour="red") +
scale_y_discrete(breaks = DILAlbum$track_name) +
scale_fill_gradient2(low = "#FF0000", midpoint=0.6,
space="Lab", mid="#FFE500", high = "#09B505") +
labs(x = "Danceability") +
labs(y = "Track Name") +
labs(title = "B'Day Album Danceability")
“I Am…Sasha Fierce”
I Am… Sasha Fierceis Beyoncé’sthird studio album. Columbia Records and Music World Entertainment released it on November 12, 2008. The album was originally released as a double album in order to advertise Beyoncé’s contradictory creative identity.
Beyonce_SF <- read_excel("~/Desktop/MEA_4600/Passion_Project/Beyonce_SF.xlsx")
View(Beyonce_SF)How many words are in this album
Beyonce_SF %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
count()## # A tibble: 1 × 1
## n
## <int>
## 1 90499049
How many times do the most popular words occur within the album
Beyonce_SF %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
head(10) %>%
knitr::kable()| word | n |
|---|---|
| halo | 67 |
| love | 66 |
| video | 64 |
| whoa | 44 |
| phone | 42 |
| baby | 39 |
| wanna | 39 |
| diva | 32 |
| ego | 32 |
| feel | 29 |
What is the sentiment of these words?
Beyonce_SF %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
inner_join(get_sentiments("bing")) %>%
inner_join(get_sentiments("afinn")) %>%
head(10) %>%
knitr::kable()| word | n | sentiment | value |
|---|---|---|---|
| love | 66 | positive | 3 |
| scared | 21 | negative | -2 |
| beautiful | 20 | positive | 3 |
| poison | 14 | negative | -2 |
| lonely | 13 | negative | -2 |
| lost | 12 | negative | -3 |
| strong | 12 | positive | 2 |
| sweet | 9 | positive | 2 |
| broken | 8 | negative | -1 |
| cool | 8 | positive | 1 |
What words stand out the most in a word cloud
Beyonce_SF %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
wordcloud2()“love”, “halo”, “video”
Loading Spotify Data
Beyonce_Spotify %>%
filter(album_name %in% "I AM...SASHA FIERCE") -> SFAlbum
View(SFAlbum)Which track in Coloring Book has the highest danceability?
Beyonce_Spotify %>%
filter(album_name %in% "I AM...SASHA FIERCE") %>%
select(danceability, album_name, track_name) %>%
kable()| danceability | album_name | track_name |
|---|---|---|
| 0.633 | I AM…SASHA FIERCE | If I Were a Boy |
| 0.511 | I AM…SASHA FIERCE | Halo |
| 0.552 | I AM…SASHA FIERCE | Disappear |
| 0.336 | I AM…SASHA FIERCE | Broken-Hearted Girl |
| 0.349 | I AM…SASHA FIERCE | Ave Maria |
| 0.306 | I AM…SASHA FIERCE | Satellites |
| 0.551 | I AM…SASHA FIERCE | Save The Hero |
| 0.426 | I AM…SASHA FIERCE | Single Ladies (Put a Ring on It) |
| 0.605 | I AM…SASHA FIERCE | Radio |
| 0.875 | I AM…SASHA FIERCE | Diva |
| 0.693 | I AM…SASHA FIERCE | Sweet Dreams |
| 0.452 | I AM…SASHA FIERCE | Video Phone |
| 0.693 | I AM…SASHA FIERCE | Why Don’t You Love Me |
| 0.632 | I AM…SASHA FIERCE | If I Were a Boy |
| 0.508 | I AM…SASHA FIERCE | Halo |
| 0.492 | I AM…SASHA FIERCE | Disappear |
| 0.336 | I AM…SASHA FIERCE | Broken-Hearted Girl |
| 0.350 | I AM…SASHA FIERCE | Ave Maria |
| 0.204 | I AM…SASHA FIERCE | Satellites |
| 0.426 | I AM…SASHA FIERCE | Single Ladies (Put a Ring on It) |
| 0.605 | I AM…SASHA FIERCE | Radio |
| 0.875 | I AM…SASHA FIERCE | Diva |
| 0.694 | I AM…SASHA FIERCE | Sweet Dreams |
| 0.479 | I AM…SASHA FIERCE | Video Phone |
| 0.632 | I AM…SASHA FIERCE | If I Were a Boy |
| 0.508 | I AM…SASHA FIERCE | Halo |
| 0.492 | I AM…SASHA FIERCE | Disappear |
| 0.336 | I AM…SASHA FIERCE | Broken-Hearted Girl |
| 0.350 | I AM…SASHA FIERCE | Ave Maria |
| 0.572 | I AM…SASHA FIERCE | Smash Into You |
| 0.384 | I AM…SASHA FIERCE | Satellites |
| 0.549 | I AM…SASHA FIERCE | That’s Why You’re Beautiful |
| 0.551 | I AM…SASHA FIERCE | Save The Hero |
| 0.426 | I AM…SASHA FIERCE | Single Ladies (Put a Ring on It) |
| 0.605 | I AM…SASHA FIERCE | Radio |
| 0.875 | I AM…SASHA FIERCE | Diva |
| 0.694 | I AM…SASHA FIERCE | Sweet Dreams |
| 0.479 | I AM…SASHA FIERCE | Video Phone |
| 0.330 | I AM…SASHA FIERCE | Hello |
| 0.623 | I AM…SASHA FIERCE | Ego |
| 0.534 | I AM…SASHA FIERCE | Scared of Lonely |
| 0.693 | I AM…SASHA FIERCE | Why Don’t You Love Me |
| 0.632 | I AM…SASHA FIERCE | If I Were a Boy |
| 0.510 | I AM…SASHA FIERCE | Halo |
| 0.492 | I AM…SASHA FIERCE | Disappear |
| 0.336 | I AM…SASHA FIERCE | Broken-Hearted Girl |
| 0.350 | I AM…SASHA FIERCE | Ave Maria |
| 0.572 | I AM…SASHA FIERCE | Smash Into You |
| 0.384 | I AM…SASHA FIERCE | Satellites |
| 0.549 | I AM…SASHA FIERCE | That’s Why You’re Beautiful |
| 0.551 | I AM…SASHA FIERCE | Save The Hero |
| 0.426 | I AM…SASHA FIERCE | Single Ladies (Put a Ring on It) |
| 0.605 | I AM…SASHA FIERCE | Radio |
| 0.875 | I AM…SASHA FIERCE | Diva |
| 0.694 | I AM…SASHA FIERCE | Sweet Dreams |
| 0.479 | I AM…SASHA FIERCE | Video Phone |
| 0.330 | I AM…SASHA FIERCE | Hello |
| 0.623 | I AM…SASHA FIERCE | Ego |
| 0.534 | I AM…SASHA FIERCE | Scared of Lonely |
| 0.632 | I AM…SASHA FIERCE | If I Were a Boy |
| 0.508 | I AM…SASHA FIERCE | Halo |
| 0.492 | I AM…SASHA FIERCE | Disappear |
| 0.336 | I AM…SASHA FIERCE | Broken-Hearted Girl |
| 0.350 | I AM…SASHA FIERCE | Ave Maria |
| 0.572 | I AM…SASHA FIERCE | Smash Into You |
| 0.384 | I AM…SASHA FIERCE | Satellites |
| 0.549 | I AM…SASHA FIERCE | That’s Why You’re Beautiful |
| 0.426 | I AM…SASHA FIERCE | Single Ladies (Put a Ring on It) |
| 0.605 | I AM…SASHA FIERCE | Radio |
| 0.875 | I AM…SASHA FIERCE | Diva |
| 0.694 | I AM…SASHA FIERCE | Sweet Dreams |
| 0.479 | I AM…SASHA FIERCE | Video Phone |
| 0.330 | I AM…SASHA FIERCE | Hello |
| 0.623 | I AM…SASHA FIERCE | Ego |
| 0.534 | I AM…SASHA FIERCE | Scared of Lonely |
| 0.632 | I AM…SASHA FIERCE | If I Were a Boy |
| 0.508 | I AM…SASHA FIERCE | Halo |
| 0.492 | I AM…SASHA FIERCE | Disappear |
| 0.336 | I AM…SASHA FIERCE | Broken-Hearted Girl |
| 0.350 | I AM…SASHA FIERCE | Ave Maria |
| 0.204 | I AM…SASHA FIERCE | Satellites |
| 0.551 | I AM…SASHA FIERCE | Save The Hero |
| 0.426 | I AM…SASHA FIERCE | Single Ladies (Put a Ring on It) |
| 0.605 | I AM…SASHA FIERCE | Radio |
| 0.875 | I AM…SASHA FIERCE | Diva |
| 0.694 | I AM…SASHA FIERCE | Sweet Dreams |
| 0.479 | I AM…SASHA FIERCE | Video Phone |
| 0.632 | I AM…SASHA FIERCE | If I Were a Boy |
| 0.508 | I AM…SASHA FIERCE | Halo |
| 0.492 | I AM…SASHA FIERCE | Disappear |
| 0.336 | I AM…SASHA FIERCE | Broken-Hearted Girl |
| 0.350 | I AM…SASHA FIERCE | Ave Maria |
| 0.204 | I AM…SASHA FIERCE | Satellites |
| 0.545 | I AM…SASHA FIERCE | Save The Hero |
| 0.426 | I AM…SASHA FIERCE | Single Ladies (Put a Ring on It) |
| 0.605 | I AM…SASHA FIERCE | Radio |
| 0.875 | I AM…SASHA FIERCE | Diva |
| 0.694 | I AM…SASHA FIERCE | Sweet Dreams |
| 0.479 | I AM…SASHA FIERCE | Video Phone |
“Diva” has the highest dancability with .875
Each track’s danceability shown in a graph
SFAlbum %>%
ggplot()+
geom_col(aes(x=track_name, y=danceability))+
theme_economist()+
theme(axis.text.x = element_text(angle = 90))
What is the distribution of the danceability within Coloring Book?
ggplot(SFAlbum, aes(x=danceability)) +
geom_density(alpha=0.7)+
labs(x="Danceability", y="Density") +
theme_economist()+
ggtitle("Distribution of Danceability Data in I Am...Sasha Fierce")
Using a heatmap code created by http://student.elon.edu/bwilliamson5/FinalProject/index.html to analyze danceability in I Am…Sasha Fierce
ggplot(data = SFAlbum, aes(x = danceability, y = track_name)) +
geom_tile(aes(fill=danceability, height=1 , width=.1),colour="red") +
scale_y_discrete(breaks = DILAlbum$track_name) +
scale_fill_gradient2(low = "#FF0000", midpoint=0.6,
space="Lab", mid="#FFE500", high = "#09B505") +
labs(x = "Danceability") +
labs(y = "Track Name") +
labs(title = "I Am...Sasha Fierce Album Danceability")
“4”
4 is the fourth studio album by American singer Beyoncé. It was released on June 24, 2011, by Parkwood Entertainment and Columbia Records.
Beyonce_4 <- read_excel("~/Desktop/MEA_4600/Passion_Project/Beyonce_4.xlsx")
View(Beyonce_4)How many words are in this album
Beyonce_4 %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
count()## # A tibble: 1 × 1
## n
## <int>
## 1 72327232
How many times do the most popular words occur within the album
Beyonce_4 %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
head(10) %>%
knitr::kable()| word | n |
|---|---|
| love | 101 |
| baby | 73 |
| run | 54 |
| tonight | 53 |
| girls | 51 |
| wanna | 45 |
| world | 41 |
| babe | 40 |
| hey | 35 |
| top | 35 |
What is the sentiment of these words?
Beyonce_4 %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
inner_join(get_sentiments("bing")) %>%
inner_join(get_sentiments("afinn")) %>%
head(10) %>%
knitr::kable()| word | n | sentiment | value |
|---|---|---|---|
| love | 101 | positive | 3 |
| top | 35 | positive | 2 |
| bad | 13 | negative | -3 |
| die | 12 | negative | -3 |
| crazy | 9 | negative | -2 |
| loved | 9 | positive | 3 |
| worry | 9 | negative | -3 |
| sucks | 8 | negative | -3 |
| miss | 7 | negative | -2 |
| promise | 7 | positive | 1 |
mix of positive and negative words. list of words changes due to which can be measured by sentiment or not.
What words stand out the most in a word cloud
Beyonce_4 %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
wordcloud2()“love”, “baby”, “girls”, “run”, “world”, “tonight”
Loading Spotify Data
Beyonce_Spotify %>%
filter(album_name %in% "4") -> FourAlbum
View(FourAlbum)Which track in the 4 has the highest danceability?
Beyonce_Spotify %>%
filter(album_name %in% "4") %>%
select(danceability, album_name, track_name) %>%
kable()| danceability | album_name | track_name |
|---|---|---|
| 0.652 | 4 | Love On Top |
| 0.648 | 4 | Party (feat. André 3000) |
| 0.799 | 4 | Schoolin’ Life |
| 0.665 | 4 | Countdown |
| 0.718 | 4 | I Miss You |
| 0.616 | 4 | Dance for You |
| 0.371 | 4 | I Care |
| 0.628 | 4 | Rather Die Young |
| 0.303 | 4 | 1+1 |
| 0.711 | 4 | End of Time |
| 0.733 | 4 | Run the World (Girls) |
| 0.545 | 4 | Best Thing I Never Had |
| 0.474 | 4 | Start Over |
| 0.510 | 4 | I Was Here |
| 0.303 | 4 | 1+1 |
| 0.371 | 4 | I Care |
| 0.718 | 4 | I Miss You |
| 0.545 | 4 | Best Thing I Never Had |
| 0.648 | 4 | Party (feat. André 3000) |
| 0.628 | 4 | Rather Die Young |
| 0.474 | 4 | Start Over |
| 0.652 | 4 | Love On Top |
| 0.665 | 4 | Countdown |
| 0.711 | 4 | End of Time |
| 0.510 | 4 | I Was Here |
| 0.733 | 4 | Run the World (Girls) |
| 0.303 | 4 | 1+1 |
| 0.371 | 4 | I Care |
| 0.718 | 4 | I Miss You |
| 0.545 | 4 | Best Thing I Never Had |
| 0.648 | 4 | Party (feat. André 3000) |
| 0.628 | 4 | Rather Die Young |
| 0.474 | 4 | Start Over |
| 0.652 | 4 | Love On Top |
| 0.665 | 4 | Countdown |
| 0.711 | 4 | End of Time |
| 0.510 | 4 | I Was Here |
| 0.733 | 4 | Run the World (Girls) |
| 0.303 | 4 | 1+1 |
| 0.371 | 4 | I Care |
| 0.718 | 4 | I Miss You |
| 0.545 | 4 | Best Thing I Never Had |
| 0.648 | 4 | Party (feat. André 3000) |
| 0.628 | 4 | Rather Die Young |
| 0.474 | 4 | Start Over |
| 0.652 | 4 | Love On Top |
| 0.665 | 4 | Countdown |
| 0.711 | 4 | End of Time |
| 0.510 | 4 | I Was Here |
| 0.733 | 4 | Run the World (Girls) |
| 0.724 | 4 | Lay Up Under Me |
| 0.799 | 4 | Schoolin’ Life |
| 0.616 | 4 | Dance for You |
| 0.650 | 4 | Run the World (Girls) - Kaskade Club Remix |
| 0.728 | 4 | Run the World (Girls) - RedTop Club Remix |
| 0.806 | 4 | Run the World (Girls) - Jochen Simms Club Remix |
“Run the World (Girls)” has the highest dancability with .806
Each track’s danceability shown in a graph
FourAlbum %>%
ggplot()+
geom_col(aes(x=track_name, y=danceability))+
theme_economist()+
theme(axis.text.x = element_text(angle = 90))
What is the distribution of the danceability within 4?
ggplot(FourAlbum, aes(x=danceability)) +
geom_density(alpha=0.7)+
labs(x="Danceability", y="Density") +
theme_economist()+
ggtitle("Distribution of Danceability Data in 4")
Using a heatmap code created by http://student.elon.edu/bwilliamson5/FinalProject/index.html to analyze danceability in 4
ggplot(data = FourAlbum, aes(x = danceability, y = track_name)) +
geom_tile(aes(fill=danceability, height=1 , width=.1),colour="red") +
scale_y_discrete(breaks = DILAlbum$track_name) +
scale_fill_gradient2(low = "#FF0000", midpoint=0.6,
space="Lab", mid="#FFE500", high = "#09B505") +
labs(x = "Danceability") +
labs(y = "Track Name") +
labs(title = "4 Album Danceability")
“BEYONCE”
Beyoncé is the eponymous fifth studio album by American singer Beyoncé. The record was released on December 13, 2013, by Parkwood Entertainment and Columbia Records. Developed as a “visual album”, its songs are accompanied by non-linear short films that illustrate the musical concepts conceived during production.
Beyonce_B <- read_excel("~/Desktop/MEA_4600/Passion_Project/Beyonce_B.xlsx")
View(Beyonce_B)How many words are in this album
Beyonce_B %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
count()## # A tibble: 1 × 1
## n
## <int>
## 1 68216821
How many times do the most popular words occur within the album
Beyonce_B %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
head(10) %>%
knitr::kable()| word | n |
|---|---|
| baby | 75 |
| love | 56 |
| girl | 52 |
| beyonc | 45 |
| hold | 44 |
| wanna | 34 |
| mine | 31 |
| cherry | 28 |
| lights | 21 |
| rock | 21 |
What is the sentiment of these words?
Beyonce_B %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
inner_join(get_sentiments("bing")) %>%
inner_join(get_sentiments("afinn")) %>%
head(10) %>%
knitr::kable()| word | n | sentiment | value |
|---|---|---|---|
| love | 56 | positive | 3 |
| heaven | 16 | positive | 2 |
| pretty | 15 | positive | 1 |
| bad | 12 | negative | -3 |
| hurts | 12 | negative | -2 |
| jealous | 10 | negative | -2 |
| shit | 8 | negative | -4 |
| haunting | 7 | negative | 1 |
| loving | 7 | positive | 2 |
| promise | 7 | positive | 1 |
What words stand out the most in a word cloud
Beyonce_B %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
wordcloud2()“baby”, “girl”, “love”, “mine”
Loading Spotify Data
Beyonce_Spotify %>%
filter(album_name %in% "BEYONCÉ [Platinum Edition]") -> BAlbum
View(BAlbum)Which track in the BEYONCÉ [Platinum Edition] has the highest danceability?
Beyonce_Spotify %>%
filter(album_name %in% "BEYONCÉ [Platinum Edition]") %>%
select(danceability, album_name, track_name) %>%
kable()| danceability | album_name | track_name |
|---|---|---|
| 0.512 | BEYONCÉ [Platinum Edition] | Pretty Hurts |
| 0.436 | BEYONCÉ [Platinum Edition] | Haunted |
| 0.589 | BEYONCÉ [Platinum Edition] | Drunk in Love (feat. Jay-Z) |
| 0.875 | BEYONCÉ [Platinum Edition] | Blow |
| 0.571 | BEYONCÉ [Platinum Edition] | No Angel |
| 0.412 | BEYONCÉ [Platinum Edition] | Partition |
| 0.589 | BEYONCÉ [Platinum Edition] | Jealous |
| 0.495 | BEYONCÉ [Platinum Edition] | Rocket |
| 0.557 | BEYONCÉ [Platinum Edition] | Mine (feat. Drake) |
| 0.470 | BEYONCÉ [Platinum Edition] | XO |
| 0.476 | BEYONCÉ [Platinum Edition] | ***Flawless (feat. Chimamanda Ngozi Adichie) |
| 0.527 | BEYONCÉ [Platinum Edition] | Superpower (feat. Frank Ocean) |
| 0.342 | BEYONCÉ [Platinum Edition] | Heaven |
| 0.459 | BEYONCÉ [Platinum Edition] | Blue (feat. Blue Ivy) |
| 0.747 | BEYONCÉ [Platinum Edition] | 7/11 |
| 0.639 | BEYONCÉ [Platinum Edition] | Flawless Remix (feat. Nicki Minaj) |
| 0.514 | BEYONCÉ [Platinum Edition] | Drunk in Love Remix (feat. Jay-Z & Kanye West) |
| 0.732 | BEYONCÉ [Platinum Edition] | Ring Off |
| 0.872 | BEYONCÉ [Platinum Edition] | Blow Remix (feat. Pharrell Williams) |
| 0.354 | BEYONCÉ [Platinum Edition] | Standing on the Sun Remix (feat. Mr. Vegas) |
| 0.512 | BEYONCÉ [Platinum Edition] | Pretty Hurts |
| 0.468 | BEYONCÉ [Platinum Edition] | Haunted |
| 0.591 | BEYONCÉ [Platinum Edition] | Drunk in Love (feat. Jay-Z) |
| 0.875 | BEYONCÉ [Platinum Edition] | Blow |
| 0.571 | BEYONCÉ [Platinum Edition] | No Angel |
| 0.447 | BEYONCÉ [Platinum Edition] | Partition |
| 0.590 | BEYONCÉ [Platinum Edition] | Jealous |
| 0.498 | BEYONCÉ [Platinum Edition] | Rocket |
| 0.556 | BEYONCÉ [Platinum Edition] | Mine (feat. Drake) |
| 0.467 | BEYONCÉ [Platinum Edition] | XO |
| 0.491 | BEYONCÉ [Platinum Edition] | ***Flawless (feat. Chimamanda Ngozi Adichie) |
| 0.527 | BEYONCÉ [Platinum Edition] | Superpower (feat. Frank Ocean) |
| 0.342 | BEYONCÉ [Platinum Edition] | Heaven |
| 0.459 | BEYONCÉ [Platinum Edition] | Blue (feat. Blue Ivy) |
| 0.747 | BEYONCÉ [Platinum Edition] | 7/11 |
| 0.645 | BEYONCÉ [Platinum Edition] | Flawless Remix (feat. Nicki Minaj) |
| 0.475 | BEYONCÉ [Platinum Edition] | Drunk in Love Remix (feat. Jay-Z & Kanye West) |
| 0.731 | BEYONCÉ [Platinum Edition] | Ring Off |
| 0.875 | BEYONCÉ [Platinum Edition] | Blow Remix (feat. Pharrell Williams) |
| 0.456 | BEYONCÉ [Platinum Edition] | Standing on the Sun Remix (feat. Mr. Vegas) |
“Blow” has the highest dancability with .875
Each track’s danceability shown in a graph
BAlbum %>%
ggplot()+
geom_col(aes(x=track_name, y=danceability))+
theme_economist()+
theme(axis.text.x = element_text(angle = 90))
What is the distribution of the danceability within BEYONCÉ [Platinum Edition]?
ggplot(BAlbum, aes(x=danceability)) +
geom_density(alpha=0.7)+
labs(x="Danceability", y="Density") +
theme_economist()+
ggtitle("Distribution of Danceability Data in BEYONCÉ [Platinum Edition]")
Using a heatmap code created by http://student.elon.edu/bwilliamson5/FinalProject/index.html to analyze danceability in BEYONCÉ [Platinum Edition]
ggplot(data = BAlbum, aes(x = danceability, y = track_name)) +
geom_tile(aes(fill=danceability, height=1 , width=.1),colour="red") +
scale_y_discrete(breaks = DILAlbum$track_name) +
scale_fill_gradient2(low = "#FF0000", midpoint=0.6,
space="Lab", mid="#FFE500", high = "#09B505") +
labs(x = "Danceability") +
labs(y = "Track Name") +
labs(title = "BEYONCÉ [Platinum Edition] Album Danceability")
“Lemonade”
Lemonade is the sixth studio album by American singer Beyoncé. It was released on April 23, 2016, by Parkwood Entertainment and Columbia Records, accompanied by a 65-minute film of the same title on HBO.
Beyonce_Lem <- read_excel("~/Desktop/MEA_4600/Passion_Project/Beyonce_Lem.xlsx")
View(Beyonce_Lem)How many words are in this album
Beyonce_Lem %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
count()## # A tibble: 1 × 1
## n
## <int>
## 1 1022010220
How many times do the most popular words occur within the album
Beyonce_Lem %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
filter(!word %in% c("vo")) %>%
head(10) %>%
knitr::kable()| word | n |
|---|---|
| beyonc | 225 |
| cut | 154 |
| love | 105 |
| slay | 49 |
| daddy | 40 |
| shot | 39 |
| black | 35 |
| closeup | 35 |
| women | 32 |
| girl | 30 |
What is the sentiment of these words?
Beyonce_Lem %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
inner_join(get_sentiments("bing")) %>%
inner_join(get_sentiments("afinn")) %>%
filter(!word %in% c("vo")) %>%
head(10) %>%
knitr::kable()| word | n | sentiment | value |
|---|---|---|---|
| love | 105 | positive | 3 |
| freedom | 21 | positive | 2 |
| hurt | 20 | negative | -2 |
| sweet | 10 | positive | 2 |
| worth | 10 | positive | 2 |
| hard | 9 | negative | -1 |
| bitch | 7 | negative | -5 |
| fuck | 7 | negative | -4 |
| broken | 6 | negative | -1 |
| crazy | 6 | negative | -2 |
What words stand out the most in a word cloud
Beyonce_Lem %>%
unnest_tokens(word, Lyric) %>%
select(word) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) %>%
filter(!word %in% c("vo")) %>%
wordcloud2()“beyonce”, “cut”, “love”, “slay”
Loading Spotify Data
Beyonce_Spotify %>%
filter(album_name %in% "Lemonade") -> LemAlbum
View(LemAlbum)Which track in the Big Day has the highest danceability?
Beyonce_Spotify %>%
filter(album_name %in% "Lemonade") %>%
select(danceability, album_name, track_name) %>%
kable()| danceability | album_name | track_name |
|---|---|---|
| 0.250 | Lemonade | Pray You Catch Me |
| 0.524 | Lemonade | Hold Up |
| 0.614 | Lemonade | Don’t Hurt Yourself (feat. Jack White) |
| 0.775 | Lemonade | Sorry |
| 0.516 | Lemonade | 6 Inch (feat. The Weeknd) |
| 0.643 | Lemonade | Daddy Lessons |
| 0.455 | Lemonade | Love Drought |
| 0.330 | Lemonade | Sandcastles |
| 0.387 | Lemonade | Forward (feat. James Blake) |
| 0.437 | Lemonade | Freedom (feat. Kendrick Lamar) |
| 0.574 | Lemonade | All Night |
| 0.896 | Lemonade | Formation |
| 0.546 | Lemonade | Sorry - Original Demo |
| 0.249 | Lemonade | Pray You Catch Me |
| 0.490 | Lemonade | Hold Up |
| 0.619 | Lemonade | Don’t Hurt Yourself (feat. Jack White) |
| 0.785 | Lemonade | Sorry |
| 0.530 | Lemonade | 6 Inch (feat. The Weeknd) |
| 0.618 | Lemonade | Daddy Lessons |
| 0.491 | Lemonade | Love Drought |
| 0.381 | Lemonade | Sandcastles |
| 0.383 | Lemonade | Forward (feat. James Blake) |
| 0.458 | Lemonade | Freedom (feat. Kendrick Lamar) |
| 0.564 | Lemonade | All Night |
| 0.733 | Lemonade | Formation |
| 0.522 | Lemonade | Sorry - Original Demo |
“Formation” has the highest dancability with .896
Each track’s danceability shown in a graph
LemAlbum %>%
ggplot()+
geom_col(aes(x=track_name, y=danceability))+
theme_economist()+
theme(axis.text.x = element_text(angle = 90))
What is the distribution of the danceability within Lemonade?
ggplot(LemAlbum, aes(x=danceability)) +
geom_density(alpha=0.7)+
labs(x="Danceability", y="Density") +
theme_economist()+
ggtitle("Distribution of Danceability Data in Lemonade")
Using a heatmap code created by http://student.elon.edu/bwilliamson5/FinalProject/index.html to analyze danceability in Lemonade
ggplot(data = LemAlbum, aes(x = danceability, y = track_name)) +
geom_tile(aes(fill=danceability, height=1 , width=.1),colour="red") +
scale_y_discrete(breaks = DILAlbum$track_name) +
scale_fill_gradient2(low = "#FF0000", midpoint=0.6,
space="Lab", mid="#FFE500", high = "#09B505") +
labs(x = "Danceability") +
labs(y = "Track Name") +
labs(title = "Lemonade Album Danceability")
Downloading all albums together for a joint analysis
Beyonce <- read_excel("~/Desktop/MEA_4600/Passion_Project/Beyonce.xlsx")
View(Beyonce)Removing any stop and soft words leaving only sentiment words left
Beyonce %>%
unnest_tokens(word, Lyric) %>%
anti_join(stop_words) %>%
count(word, sort = TRUE) -> beyonce_word_countWhat words occur the most throughout all his albums
wordcloud2(beyonce_word_count)“love”, “baby”, “time”, “cut”, “feel”
How much the 20 most common words are used throughout the albums
beyonce_word_count %>%
head(20) %>%
ggplot(aes(reorder(word, n), n)) +
geom_col() +
coord_flip() +
theme_economist()
Finding the sentiments of the most common used words throughout the albums
beyonce_word_count %>%
inner_join(get_sentiments("afinn"))-> beyonce_sentiment
View(beyonce_sentiment)What is the overall sentiment of his works
mean(beyonce_sentiment$value)## [1] -0.2714681-0.27
Are the words used in Beyonce’s lyrics positive or negative?
beyonce_word_count %>%
inner_join(get_sentiments("bing")) -> beyonce_sentiment2
View(beyonce_sentiment2)How many negative words are there in comparison to positive words?
beyonce_sentiment2 %>%
ggplot() + geom_col(aes(sentiment, n)) + theme_economist()
Overall analysis using Spotify data
| key_mode | n |
|---|---|
| C# major | 120 |
| G major | 80 |
| F# major | 58 |
| C major | 52 |
| D major | 35 |
| G# major | 35 |
| A# major | 33 |
| F major | 33 |
| F# minor | 30 |
| A minor | 27 |
C major and G major are used most often in pop music –> https://mixedinkey.com/captain-plugins/wiki/common-chord-progressions-pop-music/#
what is the most joyful Beyonce song?
Beyonce_Spotify %>%
arrange(-valence) %>%
select(track_name, valence) %>%
head(15) %>%
kable()| track_name | valence |
|---|---|
| Hip Hop Star (feat. Big Boi & Sleepy Brown) | 0.971 |
| Hip Hop Star (feat. Big Boi & Sleepy Brown) | 0.968 |
| Hip Hop Star (feat. Big Boi & Sleepy Brown) | 0.968 |
| Work It Out | 0.948 |
| Work It Out | 0.948 |
| Hold Up - Homecoming Live | 0.922 |
| Check On It (feat. Bun B & Slim Thug) | 0.922 |
| Check On It (feat. Bun B & Slim Thug) | 0.922 |
| Hold Up - Homecoming Live | 0.906 |
| If I Were a Boy - Maurice Joshua Mojo UK Remix - Main | 0.885 |
| Check On It (feat. Bun B & Slim Thug) | 0.881 |
| Diva | 0.875 |
| JA ARA E | 0.867 |
| JA ARA E | 0.867 |
| Check On It (feat. Bun B & Slim Thug) | 0.864 |
Hip Hop Star (feat. Big Boi & Sleepy Brown) is the most joyful song by Beyonce
Valence by album:
Beyonce_Spotify %>%
group_by(album_name) %>%
summarise(mean(valence)) %>%
arrange(desc(`mean(valence)`)) %>%
kable()| album_name | mean(valence) |
|---|---|
| Above And Beyoncé Dance Mixes | 0.6187875 |
| Dangerously In Love | 0.5578452 |
| Dangerously In Love (Alben für die Ewigkeit) | 0.5563875 |
| 4 | 0.5330179 |
| B’Day | 0.5313810 |
| B’Day Deluxe Edition | 0.5204405 |
| The Lion King: The Gift [Deluxe Edition] | 0.4217765 |
| I AM…SASHA FIERCE NEW DELUXE EDITION | 0.4066667 |
| I AM…SASHA FIERCE | 0.4036061 |
| Lemonade | 0.4025846 |
| HOMECOMING: THE LIVE ALBUM | 0.3929712 |
| I AM…SASHA FIERCE - Platinum Edition | 0.3848905 |
| BEYONCÉ [Platinum Edition] | 0.3727825 |
| The Lion King: The Gift | 0.3616630 |
| The Beyonce Experience Live Audio | 0.2849619 |
| I Am…World Tour | 0.2692640 |
Dangerously In Love is the most joyful album
Which album has the biggest emotional journey?
ggplot(Beyonce_Spotify, aes(x = valence, y = album_name)) +
geom_joy() +
theme_economist() +
ggtitle("Joyplot of Beyonce's joy distributions",
subtitle = "Based on valence pulled from Spotify's Web API with spotifyr")
B’Day has the biggest emotional journey and Dangerously in Love in the most joyful
Using code from https://msmith7161.github.io/what-is-speechiness/, I will be looking at how Danceability was distributed between the albums
green <- "#1ed760"
yellow <- "#e7e247"
pink <- "#ff6f59"
blue <- "#17bebb"
red <- "#d71e1e"
orange <- "#f28c07"
purple <- "#2e07f2"
brown <- "#964B00"
gray <- "#808080"
navy <- "#00205B"
teal <- "#008080"
hot_pink <- "#FF69B4"
baby_blue <- "#AED6F1"
light_purple <- "#D7BDE2"
fuscha <- "#C233FF"
forest <- "#145A32"
ggplot(Beyonce_Spotify, aes(x=danceability, fill=album_name,
text = paste(album_name)))+
geom_density(alpha=0.7, color=NA)+
scale_fill_manual(values=c(green, yellow, pink, blue, red, orange, purple, brown, gray, navy, teal, hot_pink, baby_blue, light_purple, fuscha, forest))+
labs(x="Danceability", y="Density") +
guides(fill=guide_legend(title="Album Name"))+
theme_economist()+
ggtitle("Distribution of Danceability Data")
Overall Conclusion:
From my analysis I believe Beyonce’s music has changed in correlations from life events. Her beginning albums began as girl-ish talking about love and the search for romance. We see women empowerment in her middle albums, a time when Beyonce truly knew how powerful of a business women she is, and then her last album, which featured some darker, more edgy vibes which was released in tandem with rumors of her husband’s infidelity. Though she still stayed true to her themes of pop and R&B, we can see movement from each album to the next.