P4KxSpotify: A Dataset of Pitchfork Music Reviews and Spotify Musical Features


  • Anthony T. Pinter University of Colorado Boulder
  • Jacob M. Paul University of Colorado Boulder
  • Jessie Smith University of Colorado Boulder
  • Jed R. Brubaker University of Colorado Boulder




Algorithmically driven curation and recommendation systems like those employed by Spotify have become more ubiquitous for surfacing content that people might want hear. However, expert reviews continue to have a measurable impact on what people choose to listen to and the subsequent commercial success and cultural staying power of those artists. One such site, Pitchfork, is particularly known in the music community for its ability to catapult an artist to stardom based on the review that an album receives. In this paper, we present P4KxSpotify: a dataset of Pitchfork album reviews with the corresponding Spotify audio features for those albums. We describe our data collection and dataset creation process, including the ethics of such a collection. We present basic information and descriptive statistics about the dataset. Finally, we offer several possible avenues for research that might utilize this new dataset.




How to Cite

Pinter, A. T., Paul, J. M., Smith, J., & Brubaker, J. R. (2020). P4KxSpotify: A Dataset of Pitchfork Music Reviews and Spotify Musical Features. Proceedings of the International AAAI Conference on Web and Social Media, 14(1), 895-902. https://doi.org/10.1609/icwsm.v14i1.7355