So I did a little spreadsheet with my comments and likes each time I went up a level and then had it calculate the numbers of NEW likes and comments needed for promotion. Example, I had 2,109 total likes when I first noticed I was Goblin’s Underpants, and 2,937 when I became Wrongly Accused, so 828 NEW likes. Then the spreadsheet divided the number of new likes for each level by the number required for the previous level to get an approximate idea of how the requirements get tougher. Of course each new level required more, but the data is so messy that it’s hard to tell how much. I *guess* each level takes at least 30% more points than the one before, but posssibly up to twice as many. I think the Magic Quantum Ninja Beanie Point formula probably increases the requirement for each level at the same rate, perhaps 1.5x or 2x because those are simple and intuitive rules that people are likely to pick, but at least three things probably throw off my calculations. 1: Sometimes I may not have noticed my promotion for a few days and my likes might have gone up. 2: The unknown inputs wouldn’t go up in sync with likes. 3: There are two big exceptions which I think come from bugs. 4: (??) I don’t think there were many typos in my notes because I mostly just pasted from my wall and reformatted to make the notes readable, but my Wrongly Accused Fugitive numbers look suspiciously low.

My total comments gave similar results to likes (including the 2 exceptions) except that the numbers for early levels look odd because I had several hundred comments under the old site and those show in the visible count but didn’t have any impact on the early ranking. Perhaps this means that comment counts are not part of the formula (??) or else they programmed the system to not count old-site comments so everyone would start at the same bottom level instead of giving the veterans a huge head start (??). I can post the comment counts if anyone cares.

What I want to say next won’t make sense without making you look at some raw data, so here it is — total likes, new likes and ratio (new likes for a level divided by new likes for the prior level):
0 0 n/a Candy
32 32 n/a Jang Geu-rae
106 74 2.31 Water Maid
228 122 1.65 Noble Idiot
654 426 3.49 Eunuch in Drag
1291 637 1.50 Chaebol’s Poor Doppelganger
2109 818 1.28 Goblin’s Underpants
2937 828 1.01 Wrongly Accused Fugitive
4247 1310 1.58 Errand Boy
14946 10699 8.17 Rooftop Room Dweller
29081 14135 1.32 Loan Shark
(Columns line up nicely in Notepad with fixed font. Apologies if they don’t line up on your screen)

Rooftop Room Dweller stands out like a sore thumb, and Eunuch in Drag also looks odd. Rooftop is really the point — I did my spreadsheet because I concluded a couple years ago that there had to be a bug trapping us in Errand Boy Hell and keeping us off the Rooftop for an excessively long time. And I just had to try to figure out what causes it. Catching Eunuch in Drag is just a bonus, assuming I’m right.

At first I thought it might be a simple typo when someone was typing the required points for each level, but the numbers seem to point in a different direction.

So here’s my theory (drum roll, please)…

It works out pretty well if we figure that the levels right before Eunuch and Rooftop are actually MORE THAN ONE LEVEL WITH THE SAME NAME.

If we say each new level takes twice as many points as the one before, then we get close to making sense if we say that Noble Idiot is actually 2 ranks with the same description, and Errand Boy is 3. Starting with the 1310 likes I needed to first make Errand Boy then gives a sequence of 1310 -> 2620 -> 5240 -> 10480, which is within spitting distance of the 10699 that I needed to escape Errand Boy Hell. Guessing 1.5x instead of 2x means 6 steps get you close. Probably any number between 1.2 and 2.0 would work, and my point about the likely nature of the bug doesn’t depend on what multiplier we pick.

@db-staff

This kind of mistake would be easier to make than you might think. Imagine that someone started with a word processor file or spreadsheet with a list of ranks, then wrote a program which uses a simple formula to decide when we get promoted, but which of course needs to be told which name to use for each rank. So someone copies the first name from the list and pastes it into slot 1 in the program, then tries to repeat for each new rank. Copy… paste… copy… paste…

All you need to get the bug I hypothesize is to (1) fumble the “copy” part, so you paste the same thing more than once, and (2) not carefully proof-read your program.

I’ve been known to fumble the “copy” part of copy-paste myself. It’s not hard. Repetitive copying/pasting can be mind-numbing and might turn off the proof-reading part of your brain. In a big project under time pressure sleep-deprivation might also be a factor. I’ve heard that alcohol was a factor in compiling the original list of rank descriptions, and if the ranks were put into the program soon after…

The one thing I am most nearly certain is a factor in Beanie ranks is the number of replies you have gotten, which (of course) they don’t show us and which would be a total b*tch to count up for ourselves. Sigh. The reason why I am sure those matter is the insanely high rank of DB-Staff, and the best way I can think of to explain that rank in view of their low visible stats on their page (go ahead and check it now) is that all our comments under the articles DB-Staff posts count as replies to them and hugely raise their score.

The ranks for the recappers I have checked are also consistent with this.

So the key to promotions, or at least one of the keys, is to get lots of replies. Feel free to comment. Please 🙂

Silly me. In my decades as a computer programmer being able to quickly debug programs was a vital survival skill, and so was actually looking closely at test results to spot bugs, at least for anyone who wanted to stay at the same job for a while instead of having to run away from past mistakes under pretexts like “seeking new opportunities for professional growth”. Being able to look at anomalous output and deduce what kind of bug in what part of a program might have caused it is a huge timesaver. Now my semi-retired stimulation-starved kdrama-addict ex-programmer brain just couldn’t resist trying to solve this one even though I don’t have access to the program and am really just blowing smoke.

My recent promotion finally gave me the missing data a needed, and the lack of good dramas gave me the time.

FWIW, in my fantasy ideal ranking system for ordinary users (not recappers or DB-staff) the main factor would be likes and the next would be followers, because those indicate how much everyone else appreciates what you way, and because they are relatively hard to game. Total comments could be gamed by just spamming us with lots of low-quality posts, and replies to your comments could be gamed by spamming controversial comments that others would rush to disagree with.

But I don’t want to give people ideas, so forget I ever said that.

I think one of the factors is simply how often you log in; I’m wouldn’t generally think of myself as a super prolific commenter (I have 1739 comments not counting this one which is more than I expected so maybe I am?) but I am a very regular visitor even if I don’t say anything. I’ve been at Errand Boy level for a while now – sadly I didn’t note when it happened but pretty sure it’s been over a month – time is an illusion these days so could be weeks or months 😂😬.