We have been trying to figure out ways to utilize anon feedback. One idea was to use the information to find questions that are disproportionately popular with the anon and low rep users (aka. The Long Tail).
In particular, look for questions that got a large number of anonymous feedback in relation to the total number of views. These posts are ideal candidates for aggressive maintenance.
We introduced a page on each site with some preliminary work:
https://meta.stackexchange.com/questions/greatest-hits
This list comes in 2 flavours. You can get a global list, or filter it down to questions you answered. (This allows you to gauge feedback on your own posts)
The algorithm works in the following way:
- Look at all questions with more than the median amount of views that are older than 3 months, excluding closed and locked questions.
- Sort by a modified "Views Per Day" which factors in unique anonymous and low rep feedback provided.
Views Per Day: If a post is 30 days old and it has 30 views, we consider it to have 1 view-per-day. This allows us to treat old and new questions slightly more equally.
The philosophy is that questions on the top of the list deserve some extra "love" cause they are the site's "face" to the public.
- Can you think of any ways to improve the "greatest hits" algorithm?
- How can we utilize this information to better our sites?
- Do we need any "engine level" changes to allow for improving a question/answer set?