Extraversion Could Be More Uncommon Than We Think

Statistically speaking, our friends are probably more popular than we are.

It is slightly depressing, but a simple matter of math. Because extraverted people tend to have more friends, they are disproportionately represented in social networks.

And that means everyone’s network is more extraverted than the population as a whole.

This so-called “friendship paradox” extends beyond a purely mathematical claim, documenting the phenomenon within the emerging social networks of a new class of MBA students, new research by researchers Daniel C. Feiler and Adam M. Kleinbaum of Tuck Business School at Dartmouth College says.

Network Extraversion Bias

Not only did the researchers show that extraversion bias exists in real-world networks, they found the effect is more pronounced in the networks of socially outgoing people. In other words, popular people are not immune from the friendship paradox–they experience it more intensely than others.

Feiler said:

“If you’re more extraverted, you might really have a skewed view of how extraverted other people are in general. If you’re very introverted you might actually have a pretty accurate idea.”

Feiler and Kleinbaum reached this conclusion by studying the interaction of two key factors in the formation of social networks. (1) Extraversion, which correlates with popularity, (2) Homophily, the notion that people with similar levels of extraversion are more likely to become friends.

The driving factor is homophily. Because outgoing people connect more often with fellow extraverts, their networks are more heavily weighted with extraverts. Introverts, on the other hand, are more likely to form friendships with other introverts. Their networks still display the friendship paradox, but to a lesser degree.

Societal Bias

The findings suggest there is a societal bias toward believing others are more extraverted than they actually are, and that introverts are better socially calibrated than extraverts.

“There’s a fundamental assumption in psychology that inferences about social norms are based on the people we interact with. And if that’s the case, then we need to consider that our social network is a biased sample,” Feiler says.

Kleinbaum specializes in the study of social networks, and Feiler is a behavioral scientist interested in the ways that biased samples can affect decision-making.

“We saw this opportunity to ask an interesting question, and use network science tools to speak to psychology,” Feiler says.

Feiler and Kleinbaum based their research on the emerging social networks of 284 new MBA students in the fall of 2012. Each student was surveyed twice, once at five weeks after orientation, and again at 11 weeks. Students were given a class roster and asked to indicate the people with whom they socialize.

Following the second survey, the students took the Big Five Inventory, a well-established test designed to evaluate personality traits, including extraversion.

Am I Normal?

For the most part, the data showed what Feiler and Kleinbaum expected–that network extraversion bias exists, and it is more pronounced in the networks of extraverts. The degree of bias came as something of a surprise.

“The skew gets really extreme the more extraverted you are,” Feiler says.

According to Feiler and Kleinbaum’s research, only the most introverted people–just one percent of the population–are likely to have networks that are representative of the population as a whole.

The rest of us view our social world through a distorted lens–a kind of carnival mirror that makes us feel less loved than our friends, and creates the impression that others are more social than they truly are. This could have profound effects on our job performance, relationships and self-esteem.

“There’s a tendency to wonder, ‘am I normal?'” Feiler says. “And our research suggests that you’re probably more normal than you think.”

Reference:

Popularity, Similarity, and the Network Extraversion Bias
Daniel C. Feiler, Adam M. Kleinbaum
Psychological Science April 2, 2015 0956797615569580

Photo: Mateus Lunardi Dutra