Culture  /  Study

Why are Pop Songs Getting Sadder Than They Used to Be?

The most popular songs today are sadder than they were 50 years ago: can cultural evolution explain this negative turn?

... analyse the lyrics of more than 150,000 English-language songs. These include worldwide examples, and therefore provide a wider, more diverse, sample. Here we found the same trends that we found in the Billboard dataset, so we can be confident that they can be generalised beyond top hits.

... analyse the lyrics of more than 150,000 English-language songs. These include worldwide examples, and therefore provide a wider, more diverse, sample. Here we found the same trends that we found in the Billboard dataset, so we can be confident that they can be generalised beyond top hits.

English-language popular songs have become more negative. The use of words related to negative emotions has increased by more than one third. Let’s take the example of the Billboard dataset. If we assume an average of 300 words per song, every year there are 30,000 words in the lyrics of the top-100 hits. In 1965, around 450 of these words were associated with negative emotions, whereas in 2015 their number was above 700. Meanwhile, words associated with positive emotions decreased in the same time period. There were more than 1,750 positive-emotion words in the songs of 1965, and only around 1,150 in 2015. Notice that, in absolute number, there are always more words associated with positive emotions than there are words associated with negative ones. This is a universal feature of human language, also known as the Pollyanna principle (from the flawlessly optimistic protagonist of the eponymous novel), and we would hardly expect this to reverse: what does matter, though, is the direction of the trends.


The effect can be seen even when we look at single words: the usage of ‘love’, for example, practically halved in 50 years, going from around 400 to 200 instances. The word ‘hate’, on the contrary, which until the 1990s was not even mentioned in any of the top-100 songs, is now used between 20 and 30 times each year.


Our results are consistent with other, independent analyses of song moods, some of which used completely different methodologies, and focused on other characteristics of the songs. For example, researchers analysed a dataset of 500,000 songs released in the UK between 1985 and 2015 and found a similar decrease in what they define ‘happiness’ and ‘brightness’, coupled with a slight increase in ‘sadness’. These labels resulted from algorithms analysing low-level acoustic features, such as the tempo or the tonality. The tempo and the tonality of the top-100 Billboard songs was also examined: Billboard hits have become slower, and minor tonalities have become more frequent. Minor tonalities are perceived as gloomier with respect to major tonalities. You can try this for yourself by listening to any of the YouTube examples of songs that have been digitally shifted from major to minor, or vice versa, and see how it feels: an unsettlingly happy major-shifted version of REM’s ‘Losing My Religion’ (1991) surfaces periodically on social media.

What is going on here? Discovering and describing trends is important and satisfying, but we also need to try to understand and explain them. In other words, big data needs big theory. One such big theory is cultural evolution. As the name implies, the theory stipulates that culture evolves over ...