…The ability to automatically create circles from a user’s contacts list is certainly valuable, The algorithm also has the ability to add new contacts to appropriate circles.
An important limitation, however, is the scalability of the approach. McAuley and Leskovec admit their algorithm is not particularly efficient, taking about an hour to identify ten circles from a list of 1000 Facebook contacts. That’s a lot of hours of processing for Facebook’s 1 billion users. However, they say that the technique should be quicker as broader patterns become clear once all users contacts have been taken into account.
For example, it may be possible to identify the set of all people on Facebook who went to a particular university. Then one person’s circle might consist of the intersection between this set and their contact list. Just how much of a speed up this would allow isn’t clear though.
Another important question for the future is how well in principle automatically-generated circles can be made to match ground truth circles, using only the information available in contact profiles and so on. It may be that many circles are created using information that users do not explicitly make available on social networks, such as a circle of ‘best friends’. If that’s the case, then these algorithms will never be able to reconstruct the ground truth circles perfectly. But perhaps this doesn’t matter if they provide a reasonable approximation to ground truth circles that users can tinker with at their leisure.
Another interesting approach is to look for patterns of links between contacts that users do not turn into circles—in other words connections between people that users have not recognised or want to keep hidden. Such a pattern might be linked with criminal activity, for example, or point to marketing information that could be sold.