The big news in the last week seems to be that Facebook can tell you if your relationship is going to work. No, they're not clairvoyant, it's based on research from Jon Kleinberg of Cornell University surrounding somet... Jon worked with Lars Backstrom of Facebook and researchers to organize analysis around this foundational question: given all the connections among a person's friends, can you recognize his or her romantic partner from the network structure alone?
Turns out, you can. To find out, they took data from a large sample of Facebook users - 1.3 million - and developed a new metric of connection strength: `dispersion' --- the extent to which two people's mutual friends are not themselves well-connected. The results offer methods for identifying types of structurally significant people within an individual's life... at least online.
Drawing on the theory of social foci, the researchers argue that dispersion is a structural means of capturing the idea that a friend spans many contexts in one’s social life - either because they were present through multiple life stages, or because they have been intentionally injected into multiple social circles (the way you would with a romantic relationship and/or spouse during the "meet the friends" stage).
Breaking it Down
For awhile now, we've been calling social networks "communities." You have your Twitter community, your Facebook community, etc. Following that logic, each individual's connections (the set of people to whom they are linked) form "network neighborhoods," which have been shown to have important consequences in things like social support based on network make-up and professional opportunities through created a competitive advantage that exists within connection gaps. As people increasingly use their online social networks to manage and even excel within varying aspects of their lives, the structures of their network neighborhoods reflect this.. and the associated complexity of it.
Dissecting the network neighborhood of the average online user typically shows a rather diverse set of relationships comprised of family and various types of friends - from the very close friends from childhood to the "Holiday Card" acquaintance set. Pepper in connections with current and former coworkers, members of religious communities, activities, and potentially romantic partners or the individual's spouse. When we use the available features in the data of all of these connections, we can identify the variation in the types of relationships held within the network neighborhood.
This opens up a wide application for analysis of the interface between an individual and the rest of their neighborhood: in the way they manage their own identities, how they group and identify their connections, and the information they take in from each of the groups in their networks.
Tie Strength and a Rich Tapestry of Connections
What we're looking at is something called "tie strength," which forms an important dimension allowing us to characterize a person’s links to their network neighbors. Sociologists have been actively studying this for year, and have found that the strongest ties are those "embedded" within the network neighborhood through a large number of mutual friends and extensive interaction. 'Weak' ties, by contrast, have fewer mutual friends, but that doesn't mitigate their significance. In fact, one could say it's the crux to successful relationships - because they serve as "bridges" that diversify the network neighborhood. This gives the individual access to broader perspectives, new ways of thinking and novel information - the interesting, anecdotal stuff people like to talk about.
Going back to how Facebook can predict breakups? What this research revealed is that the more well connected a couple's mutual friends were, the more likely they were to break up because it lacked dispersion: those diversified bridges. By basically sharing the same social network neighborhood (high levels of shared "embededness" and low dispersion), they essentially have less to offer because it keeps them from acting as intermediaries (the bridge) between different parts of their networks for their partner. This gives each individual in the relationship value through "if not but for" causation: it opens up new doors and experiences for their partners that they wouldn't have if not but for the relationship. But, the more shared connections a couple have, the lower the dispersement level - the less likely they are to be able to provide that value and the more likely that the relationship will ultimately implode.
Bottom line, people work best when they have their own "lives" and friends, but shared interests and relationships that respect that tend to work out the best.
Applications for Employment
It's a fascinating concept, really, and I can't help but wonder: can this be similarly applied to determine the likelihood of success of referred candidates in employment? I tend to think it can, especially for companies who are still focused on longevity of tenure vs "project-oriented" employment. As a society, we tease each other about having "work spouses" and remark that our teams can become like family because we spend so much time with them. Makes sense, when you think about the fact that we spend approximately 2/3rds of our life at work. We know that referrals often make the best hires... because the relationship with the referrer brings with it loyalty and often an increased level of performance (at least initially). The referrer doesn't want to look bad for recommending the candidate for a role and so has an investment in the relationship. The referred hire has a connection and relationship in the company which eases transition, and doesn't want to let the referrer down, so perhaps tries a bit harder in their work.
We've long since established there's a benefit to this... but when do the scales tip? Is it possible that having too many shared connections between 2 individuals at work could lead to a similar implosion in their working relationship, causing turnover? If so, could we use the dispersion theory pre-hire to analyze if there's too many shared connections to have a sustainable working relationship?
Should we be looking at the connection density and identifying useful "bridge connections" of our employees, who exist at healthy dispersion levels, as part of sourcing to produce better cultural fits and hires for our organizations? To some extent, we already are, but I think this dispersion metric and the methods to analyze it, has real application for those in Talent Attraction & Management. As making sense of "big data" continues to trend for both HR Technologists and organizations alike, being able to maximize recursive dispersion for better referral hiring certainly seems like something that bears a closer look.
As always, I would love to hear your thoughts.
Photo Sources: Top Left: Reuters/Dado Ruvic, Middle Right: 123rf.com