How do people respond to e-mails?

November 20th, 2008 - 3:14 pm ICT by IANS  

Washington, Nov 20 (IANS) Over the last decade the e-mail has grown from a novelty into a necessity. But how do people respond to e-mails? Do they respond to the most important first, making sure the process is efficient? Or do they send e-mails randomly, when they are at their computers or when they have time, without any regard to efficiency?

These are questions that Luís Amaral, associate professor of chemical and biological engineering in the McCormick School of Engineering and Applied Science at Northwestern University, and his associates set out to answer.

After studying e-mails sent and received from more than 3,000 e-mail accounts at a European university during a three-month period, they created a mathematical model that shows people send e-mail randomly, but in cycles.

Amaral said he was inspired to create such an e-mail model after a recent paper said that the rational model - where people respond to e-mails in the most efficient way - was the correct model.

“I was not convinced, since I don’t do it in a rational way,” he said. But if a random model was correct, there would be a typical interval between e-mails - which, when Amaral looked at the data, wasn’t the case. He wondered if it was possible for people to send e-mail randomly but still have non-random intervals where they didn’t send e-mail.

The answer, it turned out, was fairly simple: People don’t send e-mails when they are sleeping, according to a Northwestern release.

“During the day, you send e-mails, but then you go home, or go away for the weekend, and you don’t send e-mails,” he said. “These data were from a few years ago, and in Europe, this was especially the case, since many people didn’t have the Internet at home.”

The result was a model in which people send e-mails at random, but the probability of them sending e-mails during a given period depended on what that period was.

If it was in the middle of the night, the probability was near zero. If it was during the weekend, the probability was much lower than during weekdays.

“The model explains all the data, and it shows that people have cycles in which they use certain services,” Amaral said. . . . Even though it’s random, there are peaks in demand that don’t look random.”

The findings are published online by the Proceedings of the National Academy of Sciences.

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