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Is adding a secondary, predicted score that reflects individual taste in anime a good idea?
Feb 11, 9:46 AM
#1

Offline
Nov 2011
6335
Why do we need a secondary score?

The current MAL score is a weighted average score of all people who watched the show, irrespective of their own individual preferences for that particular genre. That means, if someone rated an anime a 10 and another a 3, MAL could give it a rating of 6, which is completely useless to both people who might genuinely enjoy the series (it's rated far below what they would have rated) as well as to the people who would never watch it (it's rated far too high for people who don't normally watch nor enjoy that type of show). Averages are just that. It's also prone to score manipulation, with people creating fake accounts simply to boost or drag down the score for a particular series.

We already had a similar suggestion before

From what I have seen, most suggestions include changing the MAL rating system to allow for decimals (so you could rate an anime a 7.2557527 for example). Another recent thread suggests showing the score breakdown by age and gender. This doesn't solve the problem of not taking into account an individual's taste, which can be wildly different even from people within the same age, gender and ethnic group. And besides, the statistics may not even be all that accurate in the first place.

What is my proposal?

Because the average MAL scores don't take into account individual preferences, my proposal here is to add a secondary score that reflects the taste of each and every individual. That means the secondary score will be different for different people. The idea is to take a weighted average score from people with similar taste to yours. MAL already have a way to measure taste similarity in the form of Affinity. The higher the affinity score, the more similar the anime taste between two users.
In essence, we could use K-nearest neighbors method from machine learning to predict how much an individual would score a given anime, where the distance is measured by the affinity levels.

Conceptually, this makes sense. That would mean if you like the harem genre, the secondary score will not consider scores from people who disliked anime of that type. Or if you like gore and blood, the score will again reflect how much people who also likes gore and blood rated the show.

Again, the idea is not to replace the average MAL score, but instead to supplement it with score relevant to your own personal taste in anime.

But MAL already has a recommendations feature

One major limitation of this feature is that a series that you enjoy might not be in the recommended list, and even if it is, you don't know how much you're likely to enjoy it because there is no scores. An anime page could have 10 'recommended' anime, but you can't tell which ones you will likely enjoy the most. Some of the recommendation can come from people with completely different tastes in anime.

The post is too long, make it short

Add a secondary score showing a prediction of how much someone would rate a show they haven't watched before based on how people with similar tastes (based on affinity level) rated the show. You could call this the 'Affinity score' or 'Predicted Score'.

What is a potential downside?

1) Because this approach relies on having enough people with similar tastes who watched and rated the anime, this might not work if there's not enough people who have rated and share a similar taste to yours. This is likely going to affect new and currently airing anime the most.

2) Another downside is that it may be more difficult to code this secondary score and could take more MAL processing resources.

By the way, K-NN is only a suggestion, there could be even better, smarter ways to implement a secondary, predicted score.
Thoughts? Do you think predicted scores based on affinity level is a good idea?
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Feb 11, 11:11 AM
#2

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Mar 2019
635
I agree.

They should just copy the way Criticker does it. They even tell you how they do it.
Feb 11, 11:29 AM
#3

Offline
Nov 2011
6335
Reply to AniMarter
I agree.

They should just copy the way Criticker does it. They even tell you how they do it.
@AniMarter I didn't know about Criticker, thanks for the link! Yea, MAL could use an approach similar to Criticker.
You can buy lossless digital music from your favorite Japanese artists on https://ototoy.jp/.
The songs are all DRM-free and you can re-download your purchased albums as you wish.
Show your support to your favorite artist if you can!
ps. if you are looking for Japanese albums, you have to search it in Japanese (not romaji). Just copy and paste the name.

For those who want to learn Japanese through anime
Resources for learning the language
Feb 11, 2:07 PM
#4

Online
Sep 2016
2980
Sure that would be helpful, but I reckon such a feature requires an IMMENSE amount of server-side resources, possibly more than everything else combined.
ZarutakuFeb 12, 2:03 AM
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Feb 14, 6:58 PM
#5

Offline
Dec 2009
9489
That is far too complicated and complex to attain with ai and MAL's database of algorithm to properly create that.
It's completely unrealistic.

Even if MAL had the best AI to formulate this, it would still be flawed. No systems can.
There are far too many variables to properly judge what anime/manga are alike when their recommendation system is flawed in itself.
Nothing would be able to produce this "accurately".

I kinda get it, but a far more realistic different option to at least have a fairer average score
would be to have an option where it filters only users who have completed the anime/manga.
Ultimately though, all and any media score averages are flawed, because not everyone has the same taste. Which I get is your point for this, but that's unfortunately not "perfectly" possible.

Unlike other anime/manga database websites who typically overrate everything, MAL actually has the best average of representation,
even if some scores are overrated or underrated for whatever reason.

... MAL wouldn't be able or willing to do this anyway if they could.
They very rarely add new features, let alone accept good suggestions.
waalex11Feb 14, 7:03 PM

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