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The Case for Musical Emotions

For many people, listening to music is a deeply emotional experience, but does that tap into universal emotions?

In a 2016 study, psychologist Heike Argstatter sought to determine whether universal basic emotions are recognizable in music across cultures. This built on her previous research which found that, within one Western culture, both trained musicians and laypeople consistently categorized the same musical sequences into categories based on the same basic emotions. Now, Dr. Argstatter sought to extend these findings to audiences in disparate cultural settings.

The study began by selecting two Western groups, from Germany and Norway, as well as two sets of non-Western participants from Indonesia and South Korea. They were then played the same musical sequences used in Dr. Argstatter’s previous work, given that this music was clearly recognized as evocative of basic emotions.

Even the written descriptions of each track in Dr. Argstatter’s study evoke strong emotions. For instance, the “anger” music is depicted as loud, fast, and showcasing rising volume or rapid fire (staccato) notes. Alternatively, the music intended to evoke happiness tended to avoid dissonance and feature an uplifting or dance-like tempo.

Overall, Dr. Argstatter found evidence that all participants, regardless of culture, would identify the same emotions in the same pieces of music. This was especially true for happiness and sadness.

However, there were marked differences between cultures, as well. For instance, one of the tracks evoking “surprise” was actually interpreted as “happiness” by the Norwegian, Korean, and Indonesian participants. Similarly, “disgust” music was classified in various ways as angry, sad, or frightening, though interestingly never happy.

Still, there were some systemic cultural differences, in that the German participants and, to a lesser degree, the Norwegian ones were consistently more likely to identify the music with its intended emotion.

Dr. Argstatter saw this as demonstrating a consistent “in-group advantage,” writing “This phenomenon is known as in-group advantage: emotional cues (e.g., faces or vocal stimuli) are better recognized if the stimuli and the participants stem from the same culture.”

It is important to note that this is not inevitable but takes some work to break through. Universal emotions, as discussed at length in this blog, are displayed in similar ways across many cultures. However, this study provides valuable insights into exactly how cultural differences do change the way emotions are expressed or recognized.

Thankfully, the study of cross-cultural differences is a specialty of the folks here at Humintell! We offer comprehensive training in improving your ability to read emotions across cultures and in communicating regardless of cultural differences.

What Makes a Good People Reader?

Humintell is here to train you as a people reader, but is there anything that could make you naturally good at this skill?

It was this question which a team of researchers, including Humintell’s Dr. David Matsumoto, sought to answer in a 2014 study. This undertaking consisted of two experiments, one on college students with no prior professional experience in reading emotions, and another on professional behavioral analysts who work in law enforcement.

Before conducting the study, its authors hypothesized that basic attributes, such as age and sex, would have a significant impact on the ability to read microexpressions. Specifically, they predicted that women would outperform men, and that youth would correlate with better people reading.

More specific personality factors were also considered, such as the role of extraversion or openness to new experiences. Similarly, they sought to test whether previous formal training actually had a positive effect or if general confidence in one’s people reading ability helped.

In order to test these hypotheses, the researchers recruited a series of university students and, after giving them relevant personality tests, exposed them to a series of images showcasing various microexpressions and asked them to determine which emotion was being expressed. One group of participants were given no relevant microexpression training, while another group was trained prior to the study.

Of those participants with no training, younger participants who were ranked as being more open to new experiences tended to be more accurate. Interestingly, those who expressed less confidence in their abilities tended to do better as well.

This became reversed for those who underwent relevant training exercises, with the more confident participants excelling. For the post-training group, age was no longer a relevant predictor, but women who were more open to new experience performed the best. Overall, those given training were able to increase accuracy over those who were not.

In order to test the role of professional experience, a second experiment was employed. This time, professional behavior analysts from the Transportation Security Administration (TSA) were recruited to see what impact this background experience would have on successful microexpression detection. Again, half were given specific training before undergoing the experiment.

For those without training, age continued to be a factor with younger officers outperforming older ones. Moreover, those given additional training before the study were significantly better than their other TSA colleagues. Contrary to the first study, moreover, personality traits and gender proved unimportant.

Another surprising finding was that those with law enforcement backgrounds before TSA were actually worse at detecting certain emotions. The study authors speculated that this is because many signs of deception are poorly understood, even by those who practice lie detection every day.

This study began a difficult process in determining whether personality traits or background are more important in the ability to read microexpressions and was unable to decide this conclusively. However, what was clear was that formal training has a major impact. Even if you are confident in your ability, or you have had to practice lie detection at work, you may not be as good at microexpression analysis as you think!

But this is what Humintell is here for! If you want to hone your skills, there is no better way than by pursuing one of our microexpression analysis courses.

Universal Basic Microexpressions?

As a follower of this blog, you are probably pretty aware of universal emotions, but how do these relate to microexpressions?

Some psychologists see microexpressions as undermining the case for basic emotions, but 2014 research conducted by Humintell’s Dr. David Matsumoto and Dr. Hyisung C. Hwang works to refute this misconception. By generating images showcasing subtle variations of basic emotions, they were able to demonstrate that study participants could consistently identify them as a given basic emotion.

This blog has discussed the notion of universal basic emotions at length, but this study asked whether more subtle facial expressions, such as microexpressions, are also reducible to basic emotional expressions or can showcase other distinctive expressions.

Such an investigation needed a precise definition of microexpressions as they relate to prototypical, universal expressions. While most of you know that a microexpression is a type of subtle expression, the study authors defined them as “low-intensity versions of full-face” expressions or as presenting the expression only in certain parts of the face, like the eyes, nose, or mouth.

In order to test this phenomenon, they derived certain facial features from universal expressions which were considered crucial to the recognition of that emotion. Then, they took faces that demonstrated basic emotions and modified them to only show some of those features.

These images were then displayed to a series of university students who were asked to examine images of those emotions which alternated between a face giving a neutral expression, a quick, one second image of that face with a subtle emotion, and then the neutral expression again. Participants were asked to identify the emotion being displayed.

Perhaps surprisingly, they found that the participants were pretty accurate in identifying the expressions, with an average 59 percent success rate across each emotion! While this may make you think that reading microexpressions is just something easy that everyone can do, this conclusion would misrepresent Dr. Matsumoto’s and Dr. Hwang’s findings.

Many of these images were derived as direct correlates of the base emotion, but some images were overladen with different subtle expressions that either didn’t correlate with an emotion or correlated with many. Where these were present, judgments became predictably less accurate.

However, there are still two major takeaways from this study. First, we can naturally identify basic emotions even at the subtle level, supporting the existence of certain universal emotional expressions. Second, we all have the ability to read microexpressions, but that this can be quite difficult.

At times where an individual is actively concealing their emotion, for instance, it will be very tricky to read, but that’s part of the reason to learn more about this subject, either through similar blog posts or through Humintell’s training programs!