Who You Could Befriend on Facebook -- It's now who you know - it's where you go that determines who you are most likely to make new friends with. That's the finding of a study by University of Cambridge researchers.
They say they have found a new way of predicting which people may become friends on social networks - based on the type of places they visit.
Their surprise finding is that going to the same gym or school or working in the same office can be more likely to bring people together than having the same friends. That may seem obvious but it has important implications for websites like Facebook or LinkedIn.
To date, most social networking sites have relied upon the ‘friend-of-a-friend’ approach to guess which people may have connections with one another.
But Salvatore Scellato, Anastasios Noulas and Cecilia Mascolo, of Cambridge’s Computer Laboratory, have a new approach that not only looks at friends of friends, but also the places people visit – with weightings given to different places such as airports and gymnasiums.
Smart thinking: Log on to Facebook and it will often suggest people you may know based on your existing friends. Now it may suggest pals you could make at your local gym
Scellato said: '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.'
The problem for social networks wanting to suggest new friends for you and increase the number of connections is the sheer volume of users. Millions of users may be good business but makes the task of recommending friends more and more difficult.
For example Facebook has 750 million active users. The two-hop approach – sharing at least a common friend –ignores the possibilities of recommending new friends based on shared places.
The research looked at the problem from the perspective of a long-standing sociological theory that people who go to the same places may be similarly-minded. That would make them individuals likely to form a connection with one another.
To test their theory, they used data from four months at a relatively small but fast-growing website called Gowalla to see how social connections grew in that time.
Scellato said: 'We discovered that about 30 per cent 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.
'By combining place friends with friends-of-friends, we can make the prediction space about 15 times smaller and yet, cover 66 per cent 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 website.' ( Dailymail.co.uk )
They say they have found a new way of predicting which people may become friends on social networks - based on the type of places they visit.
Their surprise finding is that going to the same gym or school or working in the same office can be more likely to bring people together than having the same friends. That may seem obvious but it has important implications for websites like Facebook or LinkedIn.
To date, most social networking sites have relied upon the ‘friend-of-a-friend’ approach to guess which people may have connections with one another.
But Salvatore Scellato, Anastasios Noulas and Cecilia Mascolo, of Cambridge’s Computer Laboratory, have a new approach that not only looks at friends of friends, but also the places people visit – with weightings given to different places such as airports and gymnasiums.
Smart thinking: Log on to Facebook and it will often suggest people you may know based on your existing friends. Now it may suggest pals you could make at your local gym
Scellato said: '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.'
The problem for social networks wanting to suggest new friends for you and increase the number of connections is the sheer volume of users. Millions of users may be good business but makes the task of recommending friends more and more difficult.
For example Facebook has 750 million active users. The two-hop approach – sharing at least a common friend –ignores the possibilities of recommending new friends based on shared places.
The research looked at the problem from the perspective of a long-standing sociological theory that people who go to the same places may be similarly-minded. That would make them individuals likely to form a connection with one another.
To test their theory, they used data from four months at a relatively small but fast-growing website called Gowalla to see how social connections grew in that time.
Scellato said: 'We discovered that about 30 per cent 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.
'By combining place friends with friends-of-friends, we can make the prediction space about 15 times smaller and yet, cover 66 per cent 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 website.' ( Dailymail.co.uk )
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