A new study from the University of California, Berkeley has identified and mapped the 13 subjective experiences that different kinds of music can evoke in people.
Have you ever been in a situation where you wanted a playlist of musical tracks to put you in a certain mood — for example, to motivate you to work — but were unsure how to find it or put it together?
Soon, it may become easier to find music to suit your current emotions or kickstart you into action, thanks to a new study from researchers at the University of California, Berkeley.
The research, which doctoral student Alan Cowen led, used more than 2,000 music samples to gauge how different types of music influenced emotion in cohorts from two different countries and cultures: the United States and China.
“We have rigorously documented the largest array of emotions that are universally felt through the language of music,” says the study’s senior author Prof. Dacher Keltner. The study findings now appear in PNAS.
For their study, the researchers recruited 1,591 participants from the U.S. and 1,258 participants from China, who listened to a total of 2,168 samples of different types of music.
A first experiment involved a subgroup of U.S. and Chinese participants who listened to a music library of 1,841 samples, which they rated on 11 scales assessing for broad affective features.
This primary investigation allowed the investigators to come up with a long list of possible emotional experiences that different types of music could evoke.
It also allowed the researchers to verify how participants from different cultures perceived the same subjective experiences that the music tracks elicited.
“People from different cultures can agree that a song is angry but can differ on whether that feeling is positive or negative,” notes Cowen.
Further experiments eventually led the researchers to identify a range of 13 emotions associated with music, which participants from both countries recognized.
The categories were: amusing, annoying, anxious or tense, beautiful, calm or relaxing or serene, dreamy, energizing, erotic or desirous, indignant or defiant, joyful or cheerful, sad or depressing, scary or fearful, and triumphant or heroic.
Across the spectrum, songs such as the iconic “Rock the Casbah” from the ’80s rock band The Clash made people feel more energized, and the same went for Antonio Vivaldi’s Baroque masterpiece, “The Four Seasons.”
Al Green’s 1971 single, “Let’s Stay Together,” elicited erotic feelings, while Israel Kamakawiwo’ole’s upbeat version of “Somewhere Over the Rainbow” made listening participants experience feelings of joy.
Participants tended to experience feelings of defiance when listening to heavy metal and, as the researchers had predicted, feelings of fear when they heard the track “The Murder” by Bernard Herrmann, which served as background music for the famous shower scene in Alfred Hitchcock’s film Psycho.
To make sure that participants from different cultures really did experience the same emotions when listening to certain types of music, the researchers also conducted a confirmation experiment that they had designed to eliminate, as far as possible, cultural biases.
This experiment involved asking participants to listen to more than 300 traditional instrumental tracks from both Western and Chinese cultures. The participants’ responses confirmed the findings: Listeners from both the U.S. and China reported that these tracks evoked similar emotions.
“Music is a universal language, but we don’t always pay enough attention to what it’s saying and how it’s being understood,” notes Cowen.
“We wanted to take an important first step toward solving the mystery of how music can evoke so many nuanced emotions,” he adds.
“Imagine organizing a massively eclectic music library by emotion and capturing the combination of feelings associated with each track. That’s essentially what our study has done.”
In the future, the researchers believe that their work may even have practical applications. It may help psychologists and psychiatrists develop better therapies involving music and better allow developers to program music streaming services to identify playlists that will fit the listener’s current mood.