So many people are concerned that today's technology can all too easily expose personal information - their whereabouts, habits and other intimate details about their lives. Yet those same people often reveal that same information of their own accords, on Facebook, Twitter and location-based social networking websites such as Foursquare.
While this information can be, and sometimes is, gathered and used for nefarious purposes, a group of researchers from Carnegie Mellon University's School of Computer Science say they've come up with a positive use of the data. The researchers have introduced the Livehoods project, aimed at learning more about the environment of city dwellers.
The Livehoods team has developed tools to gather information that people post on Foursquare, a site people use to "check in" and let the world know where they are located at any given moment. The team is headed by Prof. Norman Sadeh and Dr. Jason Hong; other members are Carnegie Mellon Ph.D. student Justin Cranshaw as well as Raz Schwartz, a Ph.D. student in Bar-Ilan University's Science, Technology and Society program.
Livehoods has used 18 million "check ins" to construct a map of neighborhoods as they are reflected in the real activities of smartphone users. In other words, the program can see which neighborhoods are more populated at which times. Sadeh explained that the aim of the project is to find a computerized method to analyze people's behavior as they are presented on smartphones and on the social networks."
So far the site is displaying maps of San Francisco, Pittsburgh and New York, and is calling on users to suggest other cities that should be looked at; one of the proposed cities is Tel Aviv.
The researchers are, of course, aware that there is a dark side to the tracking tools they are using. But they note that while many Internet companies try to do everything in their power to find out details about individual users, often for marketing and advertising purposes, they do not need such personal information. Instead they use general information about location to gain insight into patterns of life in different areas.
Sadeh explains that usually, urban researchers who study neighborhoods and cities base their conclusions on very static information that doesn't and cannot reveal anything about the dynamics of cities. But Livehoods gives them the ability to understand and identify things that are usually hidden, such as connections between areas and the characteristics of various areas. For example, Schwartz explained, a "neighborhood" connection has been formed between young people who live in the Williamsburg neighborhood of Brooklyn, and Union Square in Manhattan, where they usually go for entertainment.
Using this type of information, the researchers created their own map that divides the cities into living neighborhoods that are marked with various colors, denoting how many users have "checked in" to different areas. This allows them to see how the real life of a neighborhood looks, and illustrate graphically in a much simpler and easier way something that took years of research in the 1970s, said Schwartz. He added that the power of their creation lies in the fact that now, in the era of so-called big data, they can implement their tool in other cities with relative ease, whereas in the past researchers were limited to a small number of research areas. They plan to map out London prior to the opening of the Olympic Games this summer, as well as Montreal.
Dr. Yodan Rofe, an architect and city planner who lectures in the geography department at Ben-Gurion University of the Negev, said that the data displayed on the maps are not surprising. He elaborated, "They really are very similar to the old studies, which define this type of neighborhood as the 'street neighborhood,' a relatively limited area that is concentrated around your home, the neighbors you know and the nearby places that you visit daily, such as the grocery store or the nearest bus stop."
Although the maps on Livehood's site are static, the researchers say that the most interesting information will be obtained by examining the maps over a period of time. "We discovered, for example, how a new shopping center that opened on the seam line between a high class neighborhood and a poor neighborhood in Pittsburgh, which are separated by railroad tracks, caused populations that had never met before to mingle for the first time," said Cranshaw.