The cultural dynamics of music has recently become a popular avenue of research in the field of cultural evolution, reflecting a growing interest in art and popular culture more generally. Just as biologists seek to explain population-level trends in genetic evolution in terms of micro-evolutionary processes such as selection, drift and migration, cultural evolutionists have sought to explain population-level cultural phenomena in terms of underlying social, psychological and demographic factors. Primary amongst these factors are learning biases, describing how cultural items are socially transmitted from person to person. As big datasets become more openly available and workable, and statistical modelling techniques become more powerful, efficient and user-friendly, describing population-level dynamics in terms of simple, individual-level learning biases is becoming more feasible. Here we test for the presence of learning biases in two large datasets of popular song lyrics dating from 1965-2015. We find some evidence of content bias, prestige bias and success bias in the proliferation of negative lyrics, and suggest that negative expression of emotions in music, and perhaps art generally, provides an avenue for people to not only process and express their own negative emotions, but also benefit from the knowledge that prestigious others experience similarly negative emotions as they do.