My biggest concern is that the social graph is used to suggest others. This, in simplistic terms, tries to work out where a person (or 'node') lies in relation to every other person. Any other 'node' that lies near must be related, right? So if you follow someone, then that person's 'follows' must also be of interest to you.
But it has the implication that we are unidimensional. If one person who touches on a subject is of interest to us, then someone else who does the same must be? The assumption is that everyone is inter-connected and that a float number that indicates relatedness transfers to the real world. If I know person 'A' well and person 'A' knows 'person 'B' equally well, then I will probably know person 'B' well too. Except that it doesn't work like that. My colleagues might know my work self well but never have had the opportunity to meet my wife and vice versa. The 2 remain connected only through me; and then in different spheres of my life that may never coincide.
This idea is popular among engineers because it uses well-known algorithms to establish social proximity. It can be analysed, understood and relies on this assumption that is rarely questioned.
Admittedly, these are just suggestions and in no way are people forced into following total strangers; and these recommendations often do hit the target but they often fail too. And I believe that one of the causes is that recommendations based on the social graph are useful but only a part of the story.
Another part is the topic, the subjects about which a person writes. We write about what matters to us otherwise we wouldn't put the effort in. We write about things that are pertinent to our lives; irrelevant topics are not.
My argument is that relying on the social graph is good but to get closer to perfect recommendations, we need to use other ways to connect people, different types of information that can be used to find out how we relate to others, and therefore who is closely related to us as people.
One way we're doing this is at Roistr. Already, we're working on tying content together in a way that makes sense to people as a way to augment recommendations that can expand our social networks meaningfully.