Wharton's Gideon Nave discusses his research on using music to predict personality traits.

If the aggressive rap of Eminem is an auditory assault that sends you searching for smooth jazz, you’re probably a person with a high level of openness. That’s one interpretation from a study that looks at the link between music and personality. The study, by Wharton marketing professor Gideon Nave, has wide-ranging implications in our data-driven world. Companies that collect data to tailor product offerings, for example, can gain more insight by looking at their customers’ online playlists. Nave joined Knowledge at Wharton to discuss the paper, “Musical Preferences Predict Personality: Evidence from Active Listening and Facebook Likes.” The paper was co-authored with Juri Minxha of the California Institute of Technology, Michal Kosinski of Stanford University, and David M. Greenberg, Jason Rentfrow and David Stillwell of the University of Cambridge.

An edited transcript of the conversation follows.

Knowledge at Wharton: Why did you want to study the link between music preferences and our true psychologies?

Gideon Nave: We live in a time when personalized music is becoming more and more present in our life through services such as Pandora or Spotify. We know from past research that when people are given the task of getting to know each other, music is one of the first things that they tend to talk about, which suggests that music is indeed revealing something about who we are. The question at hand is, in what way can we predict people’s personalities based on their musical preferences? And what is the link between specific dimensions of musical preferences and personality dimensions?

It’s important to know that there were studies about this before, most of them using relatively small samples in populations of college students. They didn’t look at what people really listened to, their own natural behavior. In this study, we tried to use a large and diverse sample where we first asked people how much they like novel pieces of music after actually listening to them. We also looked at people’s Facebook likes.

Knowledge at Wharton: These pieces were not music they would have heard before. Tell us how you picked the music samples and made sure they fit what you were trying to study.

Nave: Yes, these were pieces of unreleased music. We know based on previous investigations that they capture a nice variance in individual musical preference between people. They consist of five different dimensions that we call music dimensions. There’s a mellow dimension, an unpretentious one, a sophisticated one, an intense one and a contemporary one.

Knowledge at Wharton: When you refer to musical preference and personality, you’re not talking about, “You like John Denver, so I don’t like you.” This is looking at deeper parts of our personalities, correct?

Nave: Yes, the musical preferences are from actual music that you listen to. In terms of personality, we use the model that is called the Big Five. It’s been the workhorse in personality psychology for over five decades. It’s based on the finding that much of the individual differences between people in personality can be explained by five main traits.

These traits are openness — people who are high in openness have more intellectual curiosity, creativity and prefer novelty and variety. The second dimension is conscientiousness. People who are more conscientious are more organized and dependable. They show self-discipline and act dutifully. They can also aim for achievement and prefer planned rather than spontaneous behavior. The third dimension is extroversion versus introversion, such that extroverts have more energy, assertiveness, sociability, and they tend to seek stimulus in the company of others.

“When people are given the task of getting to know each other, music is one of the first things that they tend to talk about.”

The other two dimensions are agreeableness — the tendency to be more compassionate and cooperative rather than suspicious and antagonistic towards others. And the last one is neuroticism, which is the opposite of emotional stability. People who are neurotic tend to experience unpleasant emotions easily, such as anger, anxiety, depression and vulnerability.

Knowledge at Wharton: What were some of your key findings?

Nave: The first overall finding was that we can predict people’s personalities from their musical preferences. We can do it most notably for openness and extroversion, but all traits were predictable. The Facebook likes did better than the actual music, and that makes sense because the Facebook likes contained more information that just the pure sound.

I think we were quite surprised to see that you can predict personality well just based on how much people rate liking very short excerpts, as short as 15 seconds in this case. The specific associations between music and personality were that the high-openness people, for example, liked mostly sophisticated music. We define this as music that is inspiring, complex and dynamic. It comprises mostly classical, operatic, world and jazz pieces.

The high-openness people, on the other hand, disliked two types of music. One of them is the mellow music, which is defined as romantic, relaxing and slow, and comprises soft rock, R&B, and adult contemporary musical pieces. High-openness people also disliked music that we defined as contemporary, which is electric, not sad, and comprises genres such as rap, electronic dance music, Latin and Europop pieces.

Extroverts, on the other hand, liked music that we called unpretentious. This represents music that is uncomplicated, relaxing and acoustic. It comprises country, folk and singer/songwriter pieces.

“We can predict people’s personalities from their musical preferences.”

Knowledge at Wharton: Besides openness and extroversion, were there correlations with other traits?

Nave: Yes. The correlations were not about specific taste for music but more for general musical preferences. For example, agreeable people showed their agreeability by just liking all of the pieces more than average. The neurotic people were less likely to like overall pieces without a specific genre involved. Conscientious was the trait that had the least predictive power from our music. Maybe the conscientious people just have other things to do.

Knowledge at Wharton: What is the value for marketers of having this type of information about our music preferences and personalities?

Nave: I think we live in a time when people are leaving their digital footprints everywhere, and we’ve learned that these digital footprints are extremely revealing about our personality traits and about who we really are. In this sense, once we have streaming services and we have more and more information about the music that people choose to listen to, we can use this to build some models of people’s personality and get to know our customers better.

Of course, this is useful for marketing, but it’s also important for privacy reasons and for policy. We have to be aware that this information, which is seemingly innocent, is actually revealing something meaningful about who we are. That potentially can lead to [firms] sending us persuasive messages that will influence our behavior, as was shown in the Cambridge Analytica scandal.

I think that this also has a lot of potential upside. Once marketers know you better, they may know which products to better match you. For example, knowing that you’re a neurotic, maybe I will want to match you with things that are good for neurotic people, such as psychotherapy or specific sports that will help people get better. On the other hand, these digital footprints are also revealing of information that can be used to exploit people. For example, think of using digital footprints in order to find people who are more likely to become compulsive gamblers. A smoking company could be looking for potential smokers.

The technology is just what it is — it can be used for the good and for the bad. Our goal as researchers is just to make it publicly available so we can judge, maybe as a society, of what is acceptable and what is not acceptable to do with it.

Knowledge at Wharton: The Cambridge Analytica controversy has sparked numerous conversations about privacy and how data should be used. How do you think that might change the game for marketers who want to use this data to target customers?

Nave: I think that, in the long run, comfort is going to trump privacy. Then the question is, what is legitimate and illegitimate to do with this data?

One of the key issues is whether we are allowed to target people individually or as groups. One of the important things that Cambridge Analytica could do is just get personalized information about specific people. Once you have people’s email addresses, for example, you can send them personalized messages, which is something that has not been done before with this capacity.

“The technology is just what it is — it can be used for the good and for the bad.”

On the other hand, targeting people with specific products or messages that match them is not a new thing. Whenever you read a golf magazine, the ads that you see in the golf magazine are intended for people who like golf and who have specific traits that golfers typically have — for example, people who are more affluent, people who have all sorts of personality or psychological profiles, specific age and so on.

I think now is a good time for society to decide where we draw the line in terms of the personalization of these messages and also what is a legitimate product or cause to promote using these very powerful techniques.

Knowledge at Wharton: It’s important to strike a balance. Customers want their privacy, but they also want things that are personalized for them. We want to feel like the brand knows who we are.

Nave:  We also don’t want to pay for the products and want to have them for free. We know that to have them for free, we need to let these companies collect data on us.  I think one of the important things is maybe the new regulations of the European Union. One of them is giving you the right to be forgotten, so you can actually tell the app if you wish it to just forget about you. I doubt most of the people will be choosing to be forgotten, but I could easily be wrong. I think this is a very good development….

Knowledge at Wharton: What’s next for this research?

Nave: There are a lot of other things besides music. There are movies, TV shows, politicians. Many people like different types of content. Another issue that we are looking at is the reasons why people like specific types of movies or music. We can do so because we have information about the lyrics or user-generated tags about the films and their scripts. We can use data-mining techniques in order to find out associations between people and specific components of the movies, such as sarcasm and topics like death, etc. This is the next thing that we’re going to look at, maybe in order to develop a more parsimonious theory that explains the findings that link Facebook likes into people’s personalities.