After analyzing the attributes of more than half a million songs released over a period of 30 years, a computer algorithm was able to sort the successful songs from also-rans with an accuracy of up to 86%.
A team of mathematicians from UC Irvine described how — and why — it accomplished this feat in a study published in Wednesday's edition of the journal Royal Society Open Science.
"Successful songs are happier, brighter, more party-like, more danceable and less sad than most songs," the team wrote.
That may sound like an obvious recipe for pop-music success. But it actually went against the dominant musical trends.
Over the decades, songs exhibited "a clear downward trend in 'happiness' and 'brightness,' as well as a slight upward trend in 'sadness,'" the study authors reported. "The public seems to prefer happier songs, even though more and more unhappy songs are being released each year."
That observation matched up with previous studies of song lyrics that found they contained fewer "positive emotions" and made more references to loneliness and social isolation as the years went by.
"It is interesting that, in this particular instance, acoustic characteristics of songs indicate similar patterns to those uncovered in lyrics," the researchers wrote.
Almost as if the music business were ignoring financial success and giving us the music they thought we deserved. Kind of like the book business, and the movie business, and the TV business, right?
And that is why I do not have TV or radio, and why I no longer frequent the bookstore.