What can cell phone data tell us about gender bias? Possibly quite a lot, as it turns out. The results of a new study published in Scientific Reports this month suggest that women are more focused on opposite-sex relationships during the reproductive years, while men are more likely to bond with a “best-friend” female at an older age and then maintain that relationship into later life. The study only analyzed cell phone contact, but it included a large sample size of 1.95 billion calls and 289 million text messages. The data was provided by a single mobile service provider in an undisclosed European country.
The analysis from the cell phone study is fascinating, suggesting all kinds of social tendencies including greater gender bias among females in intimate relationships at different stages of life. However, what may be more interesting is how the study hints at future anthropological study. Imagine the more complete picture that could be derived not just with information from cell phone activity, but also from Twitter streams, Facebook updates, geolocation data and more. Now that researchers have the tools to collect and analyze huge swaths of personal data, there is new opportunity to discover patterns of behavior and association that were previously hidden.
For example, a different study out of the New England Complex Systems Institute recently examined the social and ideological leanings of individuals who read The New York Times. That study found that readers are quite often not politically liberal, despite general assumption to the contrary.
The concept of being able to record and review human activity in digital form is nothing new. Nearly a decade ago I had the chance to work briefly with legendary computer scientist David Gelernter, who promoted the idea that we should all be able to organize our lives into digital streams, combining emails, photos, documents and more into a single, searchable timeline. However, that was long before the advent of online social networks, and the smartphone explosion. Now, we have a much broader set of connected data at our fingertips, and a far greater opportunity to analyze entire societies and sub-cultures based on the habits of day-to-day life.