Inside Rensselaer
Volume 7, No. 1, January 18, 2013
   

Study of Social Network “Check-ins” Shows That Proximity Is Still the Strongest Predictor of Friendship

The closer you live to another person, the more likely you are to be friends with that person despite the growing use and impact of social media, according to a study that drew on data from the location-based social network provider Gowalla. The study, by researchers within the Social Cognitive Networks Academic Research Center (SCNARC) at Rensselaer, also showed that people tend to move in groups of friends, and that two people chosen at random at a specific event (like a concert or at a particular store) are unlikely to be friends.

The study holds a powerful message for a broad range of applications that rely on accurate predictions of how people move, such as emergency planning, infrastructure development, communications networks, and disease control.

While the findings are seemingly common sense, the study—and continued research on social networks—holds a powerful message for a broad range of applications that rely on accurate predictions of how people move, such as emergency planning, infrastructure development, communications networks, and disease control.

“The ramifications are extremely important because if we assume that people are moving randomly, we are wrong, and therefore we will not be prepared for what people actually do,” said Boleslaw Szymanski, director of SCNARC and the Claire and Roland Schmitt Distinguished Professor of Computer Science. “Where you live really matters: Most of your friends are concentrated in the place where you live, and as the distance increases, this concentration rapidly drops.”

The findings also indicate that, even in the digital age, humans still form friendships based on personal interactions, said Tommy Nguyen, a graduate student and member of SCNARC.

“Even though, thanks to the Internet, you can be friends with anyone on the planet, the likelihood that a person will be friends with someone in a distant location chosen at random is far lower than the likelihood that this person will be friends with someone who lives in close proximity,” said Nguyen. “Proximity creates a strong boundary for who will be your friends.”

The study, titled “Using Location-Based Social Networks to Validate Human Mobility and Relationships Models,” was awarded the best paper award at the Second Workshop on Social Network Analysis in Applications held last summer in Istanbul, Turkey. The work continues the group’s recent investigations into social networks.

The current study drew on the public profiles (friends and check-ins) of 391,223 users of Gowalla collected between mid-September and late-October of 2011. Gowalla (which has since been purchased by Facebook, and is no longer available) allowed its users to share their geographic location with their friends through their smart phones in a process known as “checking in.” The users accumulated a total of around 26 million “check-ins” and 8 million friendship links. Data was provided to researchers without individual identifications to protect the privacy of users.

“When detectives want to solve a crime, they use clues to draw the big picture,” Nguyen said. “Gowalla provided the discrete location of the movements of hundreds of thousands of people—those are clues.”

The data immediately revealed that the likelihood of friendship between two people decreases as distance increases. Researchers found that 80 percent of friends of a particular person live within 600 miles of that person’s home.

The researchers also found that friends tend to move together. “If we see two people traveling together, we know first of all that social relations very much dictate our itinerary when moving over time. We cannot assume that people move randomly,” Szymanski said.

The team used the data to inform a data-driven mathematical model predicting the movement of people. Starting with a model that predicted the movements of individuals at random, they then refined the model based on the premise that each individual had friends who lived nearby, and that each individual frequently moved with their friends.

The “friends” model produced a dramatically different pattern of movement, and one far more consistent with the data they studied—data which tracked the actual movements of Gowalla users.

The “friends” model can be used in emergency management, development of infrastructure, and disease control, and can also help in building friendlier communities, with initiatives like bicycle sharing or planning the location of recreational facilities.

“People travel together, so knowing their social groups enables us to predict where they move,” Szymanski said. “In other words, our infrastructure should reflect our social ties because then it would be aligned with the movements people would make. That is a helpful insight.”

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Inside Rensselaer
Volume 7, Number 1, January 18, 2013
©2013 Rensselaer Polytechnic Institute
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