Now, however, researchers at the University of Cambridge Computer Laboratory are suggesting these social sites help people form new friendships based on the places users visit, or “check-in” — with different weightings given to the type of place.
“Essentially this is a way in which we can predict how people will make new friends. We know that we are likely to become friends with ‘friends of friends’, but what we find is there are specific places which foster the creation of new friendships and that they have specific characteristics,” said researcher Salvatore Scellato, a doctoral student at Cambridge.
The sheer volume of users is one of the biggest hurdles these social networks face while trying to make connections between people. Although millions of users is great from a business perspective, it means the task of recommending friends can become an exponentially difficult one. Facebook, for example, has 750 million active users.
The current study affirms the long-held sociological theory that people who frequently visit the same places may be similarly minded individuals who are more likely to form a connection with one another.
“For our research, we analyzed the location-based social network Gowalla to see how users created social connections over a period of four months. We discovered that about 30 percent of all new social links appear among users that check-in to the same places. Thus, these ‘place friends’ represent disconnected users becoming direct connections,” said Scellato.
“By combining place friends with friends-of-friends, we can make the prediction space about 15 times smaller and yet, cover 66 percent of new social ties.”
“It turns out that the properties of the places we interact can determine how likely we are to develop social ties. Offices, gyms and schools are more likely to aid development rather than other places such as football stadiums or airports. In those places, it’s highly unlikely people will develop a social connection.”
“Our results show it’s possible to improve the performance of link prediction systems on location-based services that can be employed to keep the users of social networks interested and engaged with that particular Web site,” said Scellato.
Source: University of Cambridge