Wide social networks make binding ties
IT'S not in the stars after all. Instead, it seems, the shape of a person's social network is a powerful signal that can identify one's spouse or romantic partner - and even if a relationship is likely to break up.
So says a new research paper written by Mr Jon Kleinberg, a computer scientist at Cornell University, and Mr Lars Backstrom, a senior engineer at Facebook.
The pair used a hefty data set from Facebook as their lab: 1.3 million Facebook users, selected randomly from among all users who are at least 20 years old, with from 50 to 2,000 friends, who list a spouse or relationship partner in their profile. That makes for a lot of social connections to analyse, roughly 379 million nodes and 8.6 billion links. The data was used anonymously.
Their key finding was that the total number of mutual friends two people share - embeddedness, in social networking terms - is actually a fairly weak indicator of romantic relationships.
Far better, they found, was a network measure that they call dispersion.
This yardstick measures not only mutual friends, but also friends from the further-flung reaches of a person's network neighbourhood. High dispersion occurs when a couple's mutual friends are not well connected to one another.
"A spouse or romantic partner is a bridge between a person's different social worlds," Mr Kleinberg explained.
Their dispersion algorithm was able to correctly identify a user's spouse 60 per cent of the time, or better than a one-in-two chance. Since everyone in the sample had at least 50 friends, merely guessing would have at best produced a one in 50 chance.
The algorithm also did pretty well with people who declare themselves to be "in a relationship", correctly identifying them a third of the time - a one in three chance compared with the one in 50 for guesswork.
Particularly intriguing is that when the algorithm fails, it looks as if the relationship is in trouble. A couple in a declared relationship and without a high dispersion on the site are 50 per cent more likely to break up over the next two months than a couple with a high dispersion, the researchers found. (Their research tracked the users every two months for two years.)
For Facebook, the research is part of its automated efforts to look more closely at the relationships among its users, in order to tailor content and ads. Mr Backstrom is the engineering manager in charge of Facebook's News Feed, which delivers content from a user's friends.
The more Facebook knows about a user's relationships, the more appropriately tailored the News Feed can be.
Therefore, much of the social-network analysis confirms what we already know: Relationships that last are ones in which the other person widens our world.