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270 points ilamont | 6 comments | | HN request time: 1.846s | source | bottom
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jasonpbecker ◴[] No.21973446[source]
Goodreads is desperately in need of a strong competitor.
replies(4): >>21973472 #>>21973686 #>>21974677 #>>21975169 #
bryanrasmussen ◴[] No.21973472[source]
Aside from the spoofing issues what are the main drawbacks and benefits of GoodReads from your perspective - what's the worst of times, what's the best of times?
replies(6): >>21973507 #>>21973634 #>>21973710 #>>21973915 #>>21973926 #>>21974301 #
1. xioxox ◴[] No.21973926[source]
The ratings are useless - any author with a devoted following gets endless 5 star reviews and YA books are stuffed with 5 star reviews. The website is clunky beyond belief and never seems to get improvements. The recommendation engine is terrible. The search facilities are weak and inconsistent. It could be so much better, but it never improves.
replies(2): >>21974337 #>>21974522 #
2. lkbm ◴[] No.21974337[source]
One thing I've noticed with the recommendation engine is that it doesn't recognize when its data set is too small. There are quite a few books where I look at the "Readers also enjoyed" list and can identify it as simply a list of other books I and one of my siblings read recently.

For example: https://www.goodreads.com/book/similar/1836622-dandelion-cap...

It's a book that my brother and I recently re-read, and the recommendations are...four other books that I and my brother read recently. Granted, the majority are the same genre, but two aren't. They're just...books we both recently gave 4 stars.

3. occamsrazorwit ◴[] No.21974522[source]
How would you fix the ratings issue? That's a common issue with ratings systems in general (that they reflect popularity instead of quality).
replies(2): >>21976489 #>>21978782 #
4. stubish ◴[] No.21976489[source]
You start by allowing people to rate the ratings. For instance, flag individual titles or tags 'not interested' such as on Steam. Even just a way to hide individual titles would make a system like Netflix much better to use, and bring product customers are more likely to pay for to the foreground. And then you can feed the data to the recommendation engines, which might start to learn about what demographics are using the system rather than relying on assumptions. My personal belief (as someone with zero actual experience here), is that dislikes and disinterest would be much better for generating recommendations over likes and interest. 'likes' just gives you what is popular in your familiar genres. 'dislikes' expresses your tastes.
replies(1): >>22088763 #
5. xioxox ◴[] No.21978782[source]
Yes - it's a difficult problem. It must be possible to build a better statistical model of each rater, in order to weight their opinions. A first step would be to normalise the rating distribution of each person (e.g. by average and standard deviation). I wouldn't use a rating for a particular book, unless the rater had some minimum number of ratings, or a book had very few ratings.
6. occamsrazorwit ◴[] No.22088763{3}[source]
If you allow people to rate the ratings, you come back to the original issue that people are unreliable raters.

Dislikes over likes does sound interesting though.