How To Use Email To Determine If Someone Likes You

Email has influenced the kinds of people we interact with. A new study by Stefan Wuchty and Brian Uzzi at Northwestern University claims that we exchange the highest volume of email with the people we know the least.

“These are folks you almost certainly wouldn't talk to on the phone,” Mr. Uzzi says. “You also probably wouldn't bump into them on the street. But email allows us to communicate with them all day long.”

What's most interesting is that “looking at the speed of a reply was more than enough” to predict the nature of a given relationship. People respond slower to people they know better. On average, people respond to close friends within seven hours of receiving an email. Professional contacts, on the other hand, took even more time: eleven hours. “But,” writes Jonah Lehrer in the WSJ, “the biggest difference came when the scientists looked at those people we barely know. On average, it took us 50 hours to reply. In other words, there's a surprisingly easy way to figure out how you feel about someone—just count the hours before you hit the “reply” button.”

“Although these messages [from people we don't know well] account for the majority of messages, people replied much more slowly to them,” Mr. Uzzi says. “We clearly give email priority to our close friends, just as we do in real life.”

Lehrer concludes, “in a world transformed by digital devices, the most important things remain constant. Although we can interact with anyone, we still respond most quickly to our closest friends. We now know many more people, but we haven't forgotten which members of our circle really matter.”


Digital communication data has created opportunities to advance the knowledge of human dynamics in many areas, including national security, behavioral health, and consumerism. While digital data uniquely captures the totality of a person's communication, past research consistently shows that a subset of contacts makes up a person's “social network” of unique resource providers. To address this gap, we analyzed the correspondence between self-reported social network data and email communication data with the objective of identifying the dynamics in e-communication that correlate with a person's perception of a significant network tie. First, we examined the predictive utility of three popular methods to derive social network data from email data based on volume and reciprocity of bilateral email exchanges. Second, we observed differences in the response dynamics along self-reported ties, allowing us to introduce and test a new method that incorporates time-resolved exchange data. Using a range of robustness checks for measurement and misreporting errors in self-report and email data, we find that the methods have similar predictive utility. Although e-communication has lowered communication costs with large numbers of persons, and potentially extended our number of, and reach to contacts, our case results suggest that underlying behavioral patterns indicative of friendship or professional contacts continue to operate in a classical fashion in email interactions.

Wuchty S, Uzzi B (2011) Human Communication Dynamics in Digital Footsteps: A Study of the Agreement between Self-Reported Ties and Email Networks. PLoS ONE 6(11): e26972. doi:10.1371/journal.pone.0026972