Every fall semester, I ask my students to anonymously share their favorite music track with me. I did the same this year before leaving for the Economic Science Association North America meeting in Tucson, Arizona. I had a 90-minute drive from Auburn to the Atlanta airport, several hours of wait time before boarding the plane, and I knew the return trip would be about the same. So, I would have plenty of time to listen to my students’ favorite tracks.
I sent a Qualtrics survey to nearly 100 students I teach this semester with this request:
Assume you have an opportunity to insert a music track into the next Voyager Golden Record to be sent into deep space. What would that ONE track be?
The response rate was more than 50%, which made me happy! (As a behavioral economist, I usually appreciate anything above a 15% response rate.:)
I always want to connect with my students and learn about their worldviews, tastes, and personalities. Unfortunately, teaching large classes makes that practically impossible. But one favorite track can reveal a lot about a person — cultural background, lifestyle, mood, or even how they see the world.
After all, the language of music is universal, and feelings often communicate more than words ever could.
After listening to the playlist, I started thinking about music preferences. Tastes are personal and multidimensional — but as an applied economist, I love quantifying things. Of course, you might think it’s a fool’s errand to convert feelings into numbers. Nevertheless, we can always try.
So, I began searching for ways to analyze songs. It turns out Spotify has been doing this for years. Using Spotify’s metrics, I was able to measure several key attributes of my students’ favorite tracks.
Let’s start with genres. Most of the tracks can be classified as Country, though this category includes many subgenres — Red Dirt, Texas Country, Alt-Country, Outlaw Country, and so on.
The second most common genre is Rock (including Classic Rock, Metal, and Southern Rock), followed by Pop.
Next, I looked at six key musical attributes that Spotify provides: danceability, energy, loudness, speechiness, acousticness, and valence:
For all six metrics, 0 represents the lower end and 1 represents the maximum value. As you can see, there’s quite a bit of diversity in my students’ musical preferences. But how do they compare to population-level trends?
Fortunately, I found a great blog post by Ahsieh (2024) that visualizes how these attributes have changed over time:
Overall, my students’ music taste attributes are very close to population averages. They prefer energetic and emotionally charged music that makes them move. Speechiness and acousticness are low, but that aligns with the general evolution of music tastes.
###🚀 The Playlist
If you’re curious about the tracks, you can listen to them here: