AideRSS aims to resolve a problem, so called “information overload”, one of the typical symptoms in 2.0 era is we are overwhelmed by the piled thousands of unread posts in Google Reader and it so hard to catch up the pace of the rest of the world. AideRSS ranks the posts to Good, Great_and _Best categories based on its PostRank. This approach moves one step forward to relieve the pain, but still does not to resolve the problem.
PostRank measures the attention, not the value
Though the algorithm of PostRank is not disclosed as the mysterious PageRank, from the promotion voucher and personal observation, the PostRank is determined by the comments, reference and social bookmarking. In another word, a provocative flaming post may invite more attention, and achieves a higher PostRank then a plain HOWTO, though the latter is more valuable imho.
PostRank reflects the group wisdom, not the personal choice
I once read digg’s program channel, then moved on to programming@reddit because the latter is more programmer-oriented and just meets my flavor. Once the community grows big, the voice from the majority dwarf the “long tail” which the minority audience care most. The same dilemma also applies to the PostRank.
PostRank is too humble
There is no evidence, still my wild guess; the PostRank is feed-based, not internet-wise as PageRank. This assumption is quite reasonable: the global PostRank is too expensive for a startup company; the global PostRank is too provocative to the bloggers, how come the post in Gizmodo ends up lower than the alternative Engadget? The humbleness renders the sorting across feeds less useful.
The next step towards perfection
To address the above issues, the PostRank needs to be personalized. Let the user to define what is Good, Great, Best based on his/her historic behavior; check the influence from the public using the popularity contest score; discover the similar minority for sharing and referring.
A hybrid Bayesian classifier case + Web 2.0 community.