[ Back to EurekAlert! ]

PUBLIC RELEASE DATE:
15-Jul-2014

[ | E-mail ] Share Share

Contact: Casey Bayer
c.bayer@neu.edu
617-373-2592
Northeastern University
www.twitter.com/Northeastern

Do women talk more than men? It's all about context

Use of sociometers shows that the extent that women are more talkative and collaborative than men depends on the situation

IMAGE: Professor David Lazer's research is focused on using technology to study social interactions on a large scale.

Click here for more information.

We've all heard the stereotype: Women like to talk. We bounce ideas off each other about everything from career moves to dinner plans. We hash out big decisions through our conversations with one another and work through our emotions with discussion.

At least, that's what "they" say. But is any of it actually true? A new study from Northeastern University professor David Lazer's lab says it isn't that simple.

Lazer, who researches social networks and holds joint appointments in the Department of Political Science and the College of Computer and Information Sciences, took a different approach. Using so-​​called "sociometers" – wearable devices roughly the size of smartphones – the researchers collected real-​​time data about the user's social interactions. Lazer's team was able to tease out a more accurate picture of the talkative-​​woman stereotype we're so familiar with—and they found that context plays a large role.

But can we really make such sweeping generalizations about the communication patterns of women versus those of men? The research is surprisingly thin considering the strength of the stereotype: Some studies say yes, women are more talkative than men. Others say there's no pattern at all. Still others say men are even bigger chatterboxes.

Perhaps all this contradiction comes from the difficulty of studying such a phenomenon. Most of these studies rely on either self-​​reported data, in which researchers gather information by asking subjects about their past conversational exploits, or observational data, in which researchers watch the interactions directly. But both of these approaches bring with them some hefty limitations. For one thing, our memories are not nearly as good as we like to think they are. Secondly, researchers can only observe so many people at once, meaning large data sets, which offer the most statistical power to detect differences, are hard to come by. Another challenge with direct observation is that subjects may act in a more affiliative manner in front of a researcher.

The research was published Tuesday in the journal Scientific Reports and represents one of the first academic papers to use sociometers to address this kind of question. The research team includes Jukka-​​Pekka Onnela, who previously worked in Lazer's lab and is now at the Harvard School of Public Health, as well as researchers at the MIT Media Laboratory and the Harvard Kennedy School.

For their study, Lazer's research team provided a group of men and women with sociometers and split them in two different social settings for a total of 12 hours. In the first setting, master's degree candidates were asked to complete an individual project, about which they were free to converse with one another for the duration of a 12-​​hour day. In the second setting, employees at a call-​​center in a major U.S. banking firm wore the sociometers during 12 one-​​hour lunch breaks with no designated task.

"In the one setting that is more collaborative we see the women choosing to work together, and when you work together you tend to talk more," said Lazer, who is also co-​​director of the NULab for Texts, Maps, and Networks, Northeastern's research-​​based center for digital humanities and computational social science. "So it's a very particular scenario that leads to more interactions. The real story here is there's an interplay between the setting and gender which created this difference."

###



[ Back to EurekAlert! ] [ | E-mail Share Share ]

 


AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.