New spotifyr R Package Release

Thu, 17 Jun 2021 08:10:00 +0200

The package is an excellent starting to point for R newbies to try their hands on musicology analysis with a few keystrokes. And of course, it is an essential part of the research infrastructure of musicology worldwide in far more advanced applications.

I have been a very long-time user of Charlie Thomson’s spotifyr R package, which is probably the most used open-source music analytics software in the world. It provides programmatic access to the Spotify Web API, which contains access to the former Echo Nest quantitative musicology engine.

It is an essential part of the Digital Music Observatory’s streaming analysis and our Listen Local apps designed for our trustworthy AI experiments and independent artist services. I am extremely proud to announce that after a very thorough modernization of the package’s exception handling, documentation, and code dependencies that I did in the last week, the package has passed again the peer-review standards and it is back on CRAN.

Getting Started

You should start with the README and get your Spotify Web API access tokens to get started.

What Was the Beatles' Favorite Key?

library(spotifyr)
beatles <- get_artist_audio_features('the beatles')

library(dplyr)
library(purrr)
library(knitr)

beatles %>% 
    count(key_mode, sort = TRUE) %>% 
    head(5) %>% 
    kable()

key_mode	n
C major	104
D major	98
G major	82
A major	76
E major	62

Get your most recently played tracks

library(lubridate)

get_my_recently_played(limit = 5) %>% 
    mutate(
        artist.name = map_chr(track.artists, function(x) x$name[1]),
        played_at = as_datetime(played_at)
        ) %>% 
    select(
      all_of(c("track.name", "artist.name", "track.album.name", "played_at"))
      ) %>% 
    kable()

track.name	artist.name	track.album.name	played_at
A Case of You	Tristen	A Case of You	2021-06-14 09:54:44
Paper Cup	Real Estate	Paper Cup	2021-06-10 20:20:11
Wrong with You	Tristen	Wrong with You	2021-06-10 20:17:24
Animal - Edit	LUMP	Animal	2021-06-10 20:13:21
Streets Of Your Town	DOPE LEMON	Streets Of Your Town	2021-06-10 18:23:00

That’s about right…

Find Your All Time Favorite Artists

get_my_top_artists_or_tracks(type = 'artists', 
                             time_range = 'long_term', 
                             limit = 5) %>% 
    select(.data$name, .data$genres) %>% 
    rowwise %>% 
    mutate(genres = paste(.data$genres, collapse = ', ')) %>% 
    ungroup %>% 
    kable()

name	genres
Japanese Breakfast	art pop, bubblegrunge, eugene indie, indie pop, indie rock, philly indie
Haley Bonar	melancholia, stomp and holler
Balthazar	belgian indie, belgian rock, dutch indie, dutch rock, ghent indie
Buildings Breeding	indie fuzzpop
Angus & Julia Stone	australian indie folk, indie folk, stomp and holler

What could I say? I travelled Australia listening only to Angus & Julia Stone, the Buildings Breeding have been with me since I discovered them on my first iPod, in one of the first podcasts, the Indiefeed. I created my Kickstarter account back in 2010 to support Haley Bonar’s third album. And the year before I was very much into Japanese Breakfast and Balthazar.

Find your favorite tracks at the moment

get_my_top_artists_or_tracks(type = 'tracks', 
                             time_range = 'short_term', 
                             limit = 5) %>% 
    mutate(
        artist.name = map_chr(artists, function(x) x$name[1])
        ) %>% 
    select(name, artist.name, album.name) %>% 
    kable()

name	artist.name	album.name
Hot & Heavy	Lucy Dacus	Hot & Heavy
Sea Urchin	Mystic Braves	Sea Urchin
Human	Freedom Fry	Human
Hot Motion	Temples	Hot Motion
Animal - Edit	LUMP	Animal

What’s the most joyful Joy Division song?

Let’s take a look at the audio feature has to be valence, a measure of musical positivity.

joy <- get_artist_audio_features('joy division')

joy %>% 
    arrange(-valence) %>% 
    select(.data$track_name, .data$valence) %>% 
    head(5) %>% 
    kable()

track_name	valence
Passover - 2020 Digital Master	0.946
Passover - 2007 Remaster	0.941
Colony - 2020 Digital Master	0.829
Colony - 2007 Remaster	0.808
Atrocity Exhibition - 2020 Digital Master	0.790

Now if only there was some way to plot joy…

Joyplot of the emotional rollercoasters that are Joy Division’s albums

Sentify: A Shiny app

This app, powered by spotifyr, allows you to visualize the energy and valence (musical positivity) of all of Spotify’s artists and playlists.

Dope Stuff Other People Have Done with spotifyr

The coolest thing about making this package has definitely been seeing all the awesome stuff other people have done with it. Here are a few examples:

Exploring the Spotify API with R: A tutorial for beginners, by a beginner, Mia Smith

Blue Christmas: A data-driven search for the most depressing Christmas song, Caitlin Hudon

Sente-se triste quando ouve “Amar pelos dois”? Não é o único (Do you feel sad when you hear “Love for both?” You’re not alone), Rui Barros, Rádio Renascença

Using Data to Find the Angriest Death Grips Song, Evan Oppenheimer

Hierarchical clustering of David Bowie records, Alyssa Goldberg

tayloR, Simran Vatsa

Our Work with spotifyR

A key mission of our Digital Music Observatory, which is our modern, subjective approach on how the future European Music Observatory should look like, is to not only to provide high-quality data on the music economy, the diversity of music, and the audience of music, but also on metadata. The quality and availability, interoperability of metadata (information about how the data should be used) is key to build trustworthy AI systems. We rely on spotifyr to fulfil this mission.

*Join our open collaboration Music Data Observatory team as a data curator, developer or business developer.

Music Streaming: Is It a Level Playing Field?

Tue, 23 Feb 2021 11:00:00 +0100

Our article, Music Streaming: Is It a Level Playing Field? is published in the February 2021 issue of CPI Antitrust Chronicle, which is fully devoted to competition policy issues in the music industry.

The dramatic growth of music streaming over recent years is potentially very positive. Streaming provides consumers with low cost, easy access to a wide range of music, while it provides music creators with low cost, easy access to a potentially wide audience. But many creators are unhappy about the major streaming platforms. They consider that they act in an unfair way, create an unlevel playing field and threaten long-term creativity in the music industry.

Our paper describes and assesses the basis for one element of these concerns, competition between recordings on streaming platforms. We argue that fair competition is restricted by the nature of the remuneration arrangements between creators and the streaming platforms, the role of playlists, and the strong negotiating power of the major labels. It concludes that urgent consideration should be given to a user-centric payment system, as well as greater transparency of the factors underpinning playlist creation and of negotiated agreements.

You can read the entire issue and the full text of our article on Competition Policy International in pdf.

Spotify | Digital Music Observatory