October 14, 2019

predicting my yearly top songs without listening/usage data (part 2)

This is a continuation from a previous post, which can be found here. Okay, picking up where we left off! In this post we’ll dive into building a set of models that can classify each of my playlist tracks as a “top-song” or not. While this is an exploration of some boutique data, it’s also a cursory look at many of the packages found in the tidymodels ecosystem. A few posts I found useful in terms of working with tidymodels can be found here, and here. Read more

September 17, 2019

predicting my yearly top songs without listening/usage data (part 1)

question: how do tracks end up on my yearly top-100 songs playlist? Last year I dug into the spotifyr package to see if the monthly playlists I curate varied by different track audio features available from the API. This time, I’m back with some more specific questions. Maybe they’ve always done this but, Spotify creates yearly playlists for each user, meant to reflect the user’s top-100 songs. I look forward to getting one each year, but I wish I knew more about how it worked. Read more

August 11, 2018

comparing audio features from my monthly playlists, using spotifyr

The NYT has a fun interactive up this week, looking at audio features to see if popular summer songs have the same sort of “signature”. After attending a presentation earlier this year, I discovered that these same sorts of features are accessible through Spotify’s API! How people curate their collections and approach listening to music usually tells you something about them, and since seeing the presentation I’ve been wanting to take a dive into my own listening habits. Read more

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