Little big change in scoring system 🔗

In recent months, we have been receiving more feedback from you about our scoring system. Increasingly, we are seeing the problem where a single vote can put an asset's score into a different rating level.

We have therefore come up with a simple solution that we hope will help a lot to improve the distribution of ratings. Since Friday 10.9.2021, we are switching the complexity calculation in our score equation from average to median.

Previous algorithm:

Average quality * average complexity * 10

New algorithm:

Average quality * median complexity * 10

How does this change help?

Since most users rate reasonably according to our statistics, the median is much closer to the most commonly held opinion than the average. Let's look at this visually:

You can see that among the 7 ratings (color circles), there is one rating far away from the other ratings, and this single rating can shift the final score significantly from the other opinions.

The median ensures that the result is closest to the most represented opinion among users.

In this case, the final score moves lower in the result, but we have also observed the opposite effect, where for very high quality models the score is lowered in a similar way for the original algorithm and raised in the opposite way. For now, however, it is likely that for a lot of models the complexity rating is reduced - the algorithm and recalculation is the same for all creators. Because the redistribution system is relativistic, this reduction does not mean that your assets will start earning less.

We believe this change will help to make the rating of models and other types of assets more fair, where the community will prevail over the opinions of individuals and random mistakes.

Why not do the same for quality?

Given that many users rate either 10 stars if they like something, or conversely often only 1 star if they dislike something, the median value would often end up at these values.