Farooq Ansari (2020): The Spotify Audio Features Hit Predictor Dataset (1960-2019). Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:d77e74b0-66bc-47ac-8b25-5796d3084478

Dataset

• Communication and Media Studies
• Artificial Intelligence and Image Processing
• Other Language, Communication and Culture
• Cultural Studies

Audio Analysis, Audio Features, Machine Learning, Music, Spotify

1960/2019

GPL-3.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Farooq Ansari

This is a dataset consisting of features for tracks fetched using Spotify's Web API. The tracks are labeled '1' or '0' ('Hit' or 'Flop') depending on some criterias of the author. This dataset can be used to make a classification model that predicts whethere a track would be a 'Hit' or not. (Note: The author does not objectively considers a track inferior, bad or a failure if its labeled 'Flop'. 'Flop' here merely implies that it is a track that probably could not be considered popular in the mainstream.) Here's an implementation of this idea in the form of a website that I made. {http://www.hitpredictor.in/}

• 2020-04-06 first online, published, posted

4TU.Centre for Research Data

media types: application/zip, text/csv, text/plain

• https://www.kaggle.com/theoverman/the-spotify-hit-predictor-dataset