It’s a failing of aggregators that they optimize for attention concentration rather than interestingness. But is there even such a thing, objectively?
With sufficiently rich data, I think they're equivalent.
I think collaborative filtering works much better once you have a critical mass of users/data - enough that taste clusters emerge. Otherwise it just defaults to whatever's globally popular. Google Reader managed it quite well. Librarything is fantastic at it (far better than Amazon).
I wrote a simple recommendation engine for musical taste in the early 2k's (pre-last.fm), but it had very little data available to it. The result? It recommended Radiohead to everyone. (Looking back, this was my first exposure to The Bitter Lesson).