Research has shown that when speaking in front of a group, people’s attention tends to gets stuck on the most emotional faces, causing them to overestimate the group’s average emotional state. In this piece, the authors share two additional findings: First, the larger the group, the greater this attention bias. Second, the attention bias is stronger for faces expressing negative emotions than for faces expressing positive ones, meaning that our ability to judge a group’s emotional state isn’t just skewed towards more intense emotions — it is specifically biased toward more negative evaluations. Based on these findings, the authors suggest that when giving a talk or meeting a large group of people, we should attempt to intentionally scan the audience more evenly in order to counteract our natural attention biases and get a more accurate picture of the group’s overall emotional state.
Imagine yourself pitching an idea to a group of people. As you speak, you quickly scan the audience, your attention jumping from face to face. Are people smiling? Or do they look confused, bored, maybe even angry?
Facial expressions impart vital clues about people’s emotions. Whether you’re a junior employee or a C-suite executive, making these split-second judgments about how your audience is feeling is a critically important skill. But even the most emotionally intelligent among us can struggle to understand exactly how these split-second judgments are made, and more importantly, whether or not they are accurate. And this becomes even more complicated when you start trying to read social cues not just in a single person, but in a group of people.
Research shows that when looking at a group, people tend to focus on faces expressing stronger emotions — whether those emotions are positive or negative — and pay less attention to faces conveying less intense emotions. In the context of public speaking, this attentional bias can shape speakers’ impressions of how they’re being received: since people pay more attention to their more-emotionally-expressive audience members, they tend to conclude that an audience’s overall reaction is more intense than it actually is.
To better understand how these biases present (as well as how you can start to overcome them), we — together with our colleagues Timothy Sweeny, Mina Cikara and James Gross — conducted a series of studies exploring this tendency to amplify groups’ emotions. In one experiment, participants were shown images of groups of up to 12 people. The faces in the images were calibrated to each display a certain amount of emotionality, enabling us to calculate the “objective” average emotional state of group. We then asked the participants to estimate the groups’ average emotional state and compared their responses to the actual levels of emotion depicted in each image.
As expected, we found that participants consistently overestimated the emotionality of the groups. But we also found two interesting new results:
First, the larger the group, the more our participants overestimated its emotional state. Because the degree of emotionality was randomly distributed among the faces (just like real-world groups will have a random distribution of more and less emotionally expressive people), larger groups had a greater likelihood of containing highly emotional faces than smaller groups did. And since peoples’ attention tends to get stuck on those highly emotional faces, they ended up rating the larger groups as more emotional on average.
Second, participants’ overestimation of groups’ emotions was slightly greater for negative expressions, such as anger, than it was for positive expressions, such as happiness. Prior research suggests that people’s attention is naturally drawn more to faces expressing negative emotions than to faces conveying positive ones, but our study found that this effect holds for groups as well as for individuals. People’s ability to judge a group’s emotional state isn’t just skewed towards more intense emotions — it is specifically biased toward more negative evaluations.
To further understand the mechanics of this tendency to overestimate groups’ emotions, we conducted a second study in which we asked participants to evaluate a group’s emotions while tracking their gaze with an eye-tracking apparatus. We found that as participants scanned an image of a group, their gaze would consistently get stuck on more emotional faces, leading them to overweight those faces when estimating the group’s average emotional state.
Our research is early and we want to be careful in prescribing takeaways. But interestingly, this latter finding points to a potential remedy for the bias towards overestimating groups’ emotions: Because focusing on emotional faces tends to overly amplify our perceptions of a group’s emotionality, intentionally scanning more evenly across both emotional and non-emotional faces may lead to a more accurate perception of your audience. We also suspect that the tendency to amplify strong emotional responses may be especially salient in virtual contexts, since you may be even more likely to miss weaker emotional signals on a screen than in person (thought this is a speculation that would require further research to confirm).
So next time you pitch an idea, give a talk, or even just enter a room and start getting a sense of the atmosphere, try actively looking at everyone, rather than letting your focus get drawn to just one or two highly emotional faces. While it won’t completely eradicate your natural attention biases, it should leave you with a more accurate estimation of how your audience really feels.