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Recommended Flaw: 31% of Digg Homepage submitted by 10 Users

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Re: Recommended Flaw: 31% of Digg Homepage submitted by 10 Users

#21
post #4

It looks like the number on News.YC is about 26%. > (let bys (map [_ 'by] (beststories nil 1000)) (/ (apply + (map cadr (firstn 10 (sort (compare > cadr) (dedup (map [list _ (count _ bys)] bys)))))) 1000)) .258 This is the fraction of the 1000 top-scoring stories in the past month or so ( http://news.ycombinator.com/best ) submitted by the top 10 submitters. Who incidentally are: nickb 77 edw519 34 markbao 26 bdfh42…

To me the percentage itself isn't surprising but the ratio percent of stories on homepage by top 10 -------------------------------------------- percent of stories submitted total by top 10 might be interesting, especially compared with percent of stories on homepage by non-top n ----------------------------------------------- percent of stories submitted total by non-top n It would reveal if top submitters are just…

very true - that would be enlightening.

You can see something similar at http://top.searchyc.com/points_per_submission . That shows you the top users (on YC at least) by points per submission.

http://top.searchyc.com/points_per_comment is even more interesting in my opinion

Re: Recommended Flaw: 31% of Digg Homepage submitted by 10 Users

#22
post #20

Earlier quoted context omitted.

What are "top" stories? My front page shows 100 stories on reddit -- the default is higher than Digg right? I do trust that Reddit does have a more robust top-user base, but I'm curious about the context.

A "top" link is a link that has been the hottest link on all of reddit at some point. There isn't really an analogous concept on Digg since there is no notion of hottness and links don't rise and fall. Links just appear at the top of the front page at some point.

An interesting comparison would be the last n articles that have been ranked <= 25 for the default sub-reddit mix. At least that would compare the articles a user would see on each frontpage without customization.

Re: Recommended Flaw: 31% of Digg Homepage submitted by 10 Users

#24
post #20

Earlier quoted context omitted.

A "top" link is a link that has been the hottest link on all of reddit at some point. There isn't really an analogous concept on Digg since there is no notion of hottness and links don't rise and fall. Links just appear at the top of the front page at some point.

An interesting comparison would be the last n articles that have been ranked <= 25 for the default sub-reddit mix. At least that would compare the articles a user would see on each frontpage without customization.

Well to answer my own question (close enough anyway) the top 10 submitters of the top 500 submissions this week account for 15.2% of articles, for this month its 15.8%

Re: Recommended Flaw: 31% of Digg Homepage submitted by 10 Users

#26
This is really old news. It first broke end of March with this post: http://socialalerter.com/news/digg-got-it-166-wrong

What's interesting is what happened after Digg's algo change in January. That algo change was supposed to increase diversity of users making the front page. It had the exact opposite effect.

Re: Recommended Flaw: 31% of Digg Homepage submitted by 10 Users

#27

This is really old news. It first broke end of March with this post: http://socialalerter.com/news/digg-got-it-166-wrong What's interesting is what happened after Digg's algo change in January. That algo change was supposed to increase diversity of users making the front page. It had the exact opposite effect.

How can it be "old news" when the Recommendation Engine only recently got released?

Re: Recommended Flaw: 31% of Digg Homepage submitted by 10 Users

#28
post #27

This is really old news. It first broke end of March with this post: http://socialalerter.com/news/digg-got-it-166-wrong What's interesting is what happened after Digg's algo change in January. That algo change was supposed to increase diversity of users making the front page. It had the exact opposite effect.

How can it be "old news" when the Recommendation Engine only recently got released?

Because the data has been available for ages. The Recommendation Engine has little to do with going popular - yet.

In the future when we have thousands of new stories published after the Recommendation Engine being available for everyone, the same analysis would be very interesting to do again then.

It boils down to whether you have enough data or not.

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