Tag: R

Louder, Faster, Harder, Stronger: The Loudness War

If you’re in the music industry or if you nerd out on music, you would have heard of the Loudness War.

The concept is fairly intuitive: the louder the song, the more likely people will hear it, especially when they aren’t paying active attention. Being loud helps a song get noticed when it’s on the radio during your cab ride or at the grocery store. If your song is louder than your rival’s, it gets the listener’s attention, and people are more likely to remember it the next time they are streaming or buying music.

The tradeoff is that when you make a song louder, you sacrifice sound quality. In the process of boosting the overall loudness of a song, all the sounds are made louder, including the softer sounds. The contrast between loud and soft sounds is lost, along with the nuanced interactions between different instruments and the vocals. Basically, it sounds more crappy and boring.

Why do record companies commit this atrocity? Because it sells. Music analytics company Next Big Sound analyzed the audio features of 32,310 musical tracks by 751 artists, and found that loudness is positively correlated with sales, other factors held constant.


In this contour plot, the x-axis represents loudness, and the y-axis represents sales. The weird multi-layer shape in the plot is the “contour,” which tells you where the various tracks stand in their loudness-sales relationships. The color represents the density: the blue bit indicates that a lot of tracks are clustered in that area on the graph.

Most of the songs in the sample tend to be on the loud side, as the center of the blue bit sits near the right end of the x-axis. Most songs really don’t sell that much, so a large cluster of the tracks sits low on the y-axis. The tracks that turn out to be mega hits are at the upper right corner of the plot, and they are all on the loud side.

What does this tell us? Loudness is correlated with higher sales. The relationship isn’t linear though; it looks more like a roughly log-linear (exponential) relationship.

As a consumer, I’ve adapted. I’ll just listen to the shitty loud songs at the club. At home, I’ll put on some good old classical on a curated sound system.

U.S. Mass Shooting Fatalities Since 2014


And therefore never send to know for whom the bell tolls;
It tolls for thee.

– John Donne, No Man Is An Island

This chart depicts the number of fatalities in mass shootings in the U.S. from 2014 to 2016. You can see clearly that the toll from the latest shooting in Orlando, Florida far outnumbers even the sum of a number of past shootings.

Frank Bruni sums it up pretty well. This isn’t an attack on a minority subset of a population, but an attack on the “bedrock” of our society: the very idea of democracy, acceptance, and diversity.

How many of these incidents are still going to happen before something is done? Sadly, maybe quite a few. “And to actively do nothing is a decision as well.”

You can’t really say “I’m glad this didn’t/doesn’t happen where I live.” Just because it didn’t, doesn’t mean it couldn’t.

First they came for the Socialists, and I did not speak out—
Because I was not a Socialist.

Then they came for the Trade Unionists, and I did not speak out—
Because I was not a Trade Unionist.

Then they came for the Jews, and I did not speak out—
Because I was not a Jew.

Then they came for me—and there was no one left to speak for me.
– Martin Niemöller

This is a work in progress, and the code is on GitHub. The data source is Gun Violence Archive.

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