This is a repository which hosts the source code to scrape and prepare the public version of the data set:

Datta, Hannes, 2020, "Playlist promotions and New Releases at Spotify", https://doi.org/10.34894/0RK0KK, DataverseNL.

If you are...

• a (potential) user of the data, you can download the data, or view its detailed documentation here.
• part of the maintenance team, you can use this repository to update the dataset or its documentation.
• interested in creating your own reproducible workflows for anonymizing and sharing data with the public, you can use this repository as a template.

Note: The data set is not released to the public yet (expected mid of 2021). For questions, get in touch via email, please.

This repository contains data collected with two webscrapers from everynoise.com.

(1) New releases: A list of (weekly) album and single releases to Spotify, by country

The data is scraped from everynoise.com/new_releases_by_genre.cgi.

(2) Worldbrowser: A list of "promoted"/"featured" playlists on Spotify, by playlist category, hour-of-the-day (if available), and country.

While the data is collected from everynoise.com/worldbrowser.cgi, the data actually comes directly from the Spotify Web API, which powers the browse interface of the Spotify platform.

• Obtain a valid API key from Dataverse ("API Token" in the main menu), and store it as a user's environment variable called DATAVERSE_TOKEN.
• Install Java
• Download the most recent version of the Dataverse uploading tool (run bash init.sh on Mac, or paste the link contained in the file in your browser on Windows)

├── credentials.txt         <- stores API credentials
├── doc                     <- put any documentation here
│   └── readme-template.txt (start from this template)
├── rawdata-confidential    <- folder with confidential data
├── release                 <- folder with public releases
├── src                     <- source code 
│   └── collect                (data collection) 
└────── prepare                (parsing and preparation for public release)

• Archive confidential raw data on Dataverse: push_raw.sh pushes the raw data to Dataverse (done once, bash push_raw.sh; or paste code into your command prompt on Windows). Remember to restrict access to the folder, by editing the file/directory permissions directly on Dataverse.

• Add/change data preparation code (e.g., to anonymize data) in src\; run this code yourself to produce derivate datasets for the (to-be-made public) release\ folder.

• Release public versions of the data to Dataverse: release.sh pushes (updates) to the documentation in doc\, or the prepared data set in release\.

• Done? Publish your data set on Dataverse (via the web interface).

Note: API keys used in the .sh scripts is deprecated.

First, please install...

• Python distribution via Anaconda
• Scrapy (toolkit for webscraping) pip install scrapy

Then, you can run the data collections:

• Run everynoise.py file (weekly) python everynoise.py

• Run everynoise_worldbrowser.py file (hourly) python everynoise_worldbrowser.py

The two webscrapers write the output of the data collections to JSON files.

(1) New releases

The data is written to new-line separated JSON files, named everynoise_newreleases_YYYYMMDD.json (whereas YYYYMMDD refers to the datestamp when the scraper was run. It lists the weekly releases to the Spotify platform by country. Each release is characterized by an albumId/albumName, and and associated artistName/artistId. The trackId in the data below represents a preview snipped of the album that users can click to listen to (a part) of the release. Singles are released as single-track albums.

JSON file structure

{
  "countryCode": "EC", # two-letter country code
  "trackId": "spotify:track:2rRhbOTbTwAUq45qdllfST", # Spotify track ID of a preview track of the album release
  "artistId": "spotify:artist:07YUOmWljBTXwIseAUd9TW", # Spotify artist ID of the album release
  "rank": "EC rank: 10", # Rank (probably popularity rank; exact definition is pending)
  "artistName": "Sebastián Yatra", # Artist name associated with album release
  "albumId": "spotify:album:2B4n5Uy0rYJ1btdqtUsrw8", # Spotify album ID
  "albumName": "Un Año (En Vivo)", # Album name
  "scrapeUnix": 1570447279, # Unix time stamp when the data was scraped
  "scrapeDate": "20191007", # Datestamp when the data was scraped
  "everynoiseDate": "20191004" # Date when track/album was released to Spotify
}

(2) Worldbrowser

The data is written to new-line separated JSON files, named everynoise_worldbrowser_YYYYMMDD__HHMM.json (whereas YYYYMMDD refers to the datestamp, and HHMM to the hour-minute timestamp when the scraper was run.

JSON file structure

{
  "sectionName": "featured",
  "countryName": "Global",
  "countryCode": "3",
  "playlistIdArray": [
    "spotify:playlist:37i9dQZF1DX3rxVfibe1L0",
    "spotify:playlist:37i9dQZF1DXcBWIGoYBM5M",
    "spotify:playlist:37i9dQZF1DX1s9knjP51Oa",
    "spotify:playlist:37i9dQZF1DX0XUsuxWHRQd",
    "spotify:playlist:37i9dQZF1DX4pUKG1kS0Ac",
    "spotify:playlist:37i9dQZF1DWSXBu5naYCM9",
    "spotify:playlist:37i9dQZF1DWXRqgorJj26U",
    "spotify:playlist:37i9dQZF1DX7ZUug1ANKRP",
    "spotify:playlist:37i9dQZF1DWWQRwui0ExPn",
    "spotify:playlist:37i9dQZF1DWYmmr74INQlb",
    "spotify:playlist:37i9dQZF1DX2Nc3B70tvx0",
    "spotify:playlist:37i9dQZF1DWVViFqIfGGV7"
  ],
  "scrapeUnix": 1572350843,
  "scrapeDate": "20191029",
  "everyNoiseHour": "08:07am",
  "everyNoiseHourReference": "-23"
}

• SectionName: Playlist category, one of Featured, Top Lists, Pop, Hip-Hop, Mood, Decades, Country, Workout, Rock, Latin, Focus, Chill, Dance/Electronic, Tastemakers, R&B, Indie, Folk & Acoustic, Party, Wellness, Sleep, Classical, Jazz, Soul, Christian, Gaming, Romance, K-Pop, Anime, Pop culture, Arab, Desi, Afro, Comedy, Metal, Regional Mexican, Reggae, Blues, Punk, Funk, Student, Dinner, Black history is now, Spotify Singles, Commute, Kids & Family, Word, Yoga, Nature Sounds, Self love, Exercise, Meditation.
• CountryName: Country
• CountryCode: Country in numeric coding
• playlistIdArray: Spotify playlist IDs that were featured in a given category
• scrapeUnix: Unix timestamp of data retrieval (seconds passed since 1970-01-01, 00:00)
• scrapeDate: Date of data retrieval
• everyNoiseHour: Playlists from the featured category vary by hour of the day
• everyNoiseHourReference: Coding of everynoise hour category