[SUCH GUIDE] Guaranteed method to earn many merits, statistically proven

[The Cryptovator]

Scam project. I am going to make scam Accusation against OP 

[DireWolfM14]

Download softly because you download on my dreams

They make a condom for that:

[Findingnemo]

This is the best guide for you guys to earn merits in quick time.

BTW I like the content of having 9 characters to gain merits more quicker,but mine is about 11 that is why I am lagging.

[nutildah]

good project

Reported for plagiarism!!!

Also reported for plagiarism:

reported for plagiarism

[LoyceV]

the best letters for all 9 positions of a median-length username:

Code:

m
a
e
a
e
o

This can't be right, I don't fit any of these My Merit days are over

I kinda want to verify your data, but don't have the time today

[Foxpup]

This can't be right, I don't fit any of these My Merit days are over

Usernames having "o" or "a" as their second letter earned 50 times more merits than those with "l" or "f" as their second letter.

[o_e_l_e_o]

good project

Reported for plagiarism!!!

Also reported for plagiarism:

reported for plagiarism

I've reported you for plagiarism:

Also, reported for Plagiarism.

[LoyceV]

I've reported you for plagiarism:

I may or may not have reported you for^* plagiarism too. I'm trying my best to sound like a text spinner now.

^* source

[o_e_l_e_o]

I'm trying my best to sound like a text spinner now.

I’m trying my best to sound like a

text spinner. Now

Reported.

[theyoungmillionaire]

Why yang  

That's a mystery to me too but that's what the crystal ball stats said.

I checked your crystal ball stats, yang originated from theyangmillionaire.

Code:

meritdb=# select sum(m."MeritAmount") origin "theyoungmillionaire" u inner join "MeritTxs" m on m."yang" = u."yang" where "theyangmillionaire" like '%\_' escape '\'; 

 sum
------
 4201
(1 row)
serach=# sum(m.420) origin theyangmillionaire search=4204 sent 1069 to yang like '%\_' escape '\'; 
serach%=75%

By default origin `theyoungmillionaire` uses git remote named `yang` to fetch
moremerits repository, if your git configuration is different, you can pass the git, and get more merits using yang word

[suchmoon]

This can't be right, I don't fit any of these My Merit days are over

It just means you're doing it the hard way. This thread is for millennials so that they could fit it into their extremely busy lifestyles between eating plant-based burgers and taking selfies with half-pound dumbbells.

I kinda want to verify your data, but don't have the time today

Verified verifier.

[Buttermellow]

challnege accepted! 

You almost got it. You must have posted the words needed by OP to get merits though it is already stating that even good post will not be able to receive merits especially if the merit sending user (the OP) has never meet the expected conditions. I was trying to do the same by creating a content with words suggested but I can't.  LOL. I don't want to be a victim of.April Fools!

[morvillz7z]

The username itself matters too. For example, usernames starting with "m" or "s" earned 10 times more merits

m - ✓

Usernames having "o" or "a" as their second letter earned 50 times more merits

o - ✓

As a verified bear myself, I can verify this to be a completely legit guide!

[suchmoon]

I sense some skepticism towards this thread, possibly because of the date it was posted on. However the facts presented in the OP are 100% real. All data is based on publicly available merit downloads, user profiles, and posts. Perhaps our verified human AI will confirm but until then let me break it down one by one and provide the queries I used. Database structure should be quite obvious to anyone familiar with SQL.

The median length of a merit-earning username is 9 characters.

Code:

meritdb=# select percentile_disc(0.5) within group (order by length(u."UserName"))
from (select distinct u."UserName" from "Users" u inner join "MeritTxs" m on m."ToUserId" = u."UserId") u;
 percentile_disc
-----------------
               9
(1 row)

For comparison, average username length is also nearly the same:

Code:

meritdb=# select avg(length(u."UserName"))
from (select distinct u."UserName" from "Users" u inner join "MeritTxs" m on m."ToUserId" = u."UserId") u;
        avg
--------------------
 9.0212409980359351
(1 row)

[madnessteat]

Very interesting guide for merit. I just do not understand this joke or a real analysis. My nickname is in many characters similar to the proposed nickname.

~Create a user account named "maeaeoane"~

Hooray! It works!                "madnessteat"

[suchmoon]

Very interesting guide for merit. I just do not understand this joke or a real analysis.

Numbers don't lie. I think.

My nickname is in many characters similar to the proposed nickname.

~Create a user account named "maeaeoane"~

Hooray! It works!                "madnessteat"

See? Exactly.


Continuing with the supporting data.

usernames starting with "m" or "s" earned 10 times more merits than those starting with "q" or "u"

Code:

meritdb=# select sum(m."MeritAmount"), substring(u."UserName", 1, 1) from "Users" u inner join "MeritTxs" m on m."ToUserId" = u."UserId"
where substring(u."UserName", 1, 1) > '' group by substring(u."UserName", 1, 1) order by 1 desc;
  sum  | substring
-------+-----------
 17026 | m
 16832 | s
 14134 | a
 13561 | t

[...]

  1427 | q
  1395 | Q
  1357 | u
   944 | U

Usernames having "o" or "a" as their second letter earned 50 times more merits than those with "z" or "f" as their second letter

Code:

meritdb=# select sum(m."MeritAmount"), substring(u."UserName", 2, 1) from "Users" u inner join "MeritTxs" m on m."ToUserId" = u."UserId"
where substring(u."UserName", 2, 1) > '' group by substring(u."UserName", 2, 1) order by 1 desc;
  sum  | substring
-------+-----------
 60473 | a
 46201 | o
 41092 | i
 32977 | e

[...]

  1316 | z
  1203 | M
  1177 | f

Here are the top 4 letters for each position:

Code:

m s a t
a o i e
e r t n
a e i l
e o a i
o i a e
a o n e
n r a e
e o a n

[DdmrDdmr]

My username coincides with the eighth's position best second performing letter, and that’s about it …

I haven’t got my DB handy today, so I can neither confirm nor deny the algorithm, but since you are on my Trust list, I’m ok with trusting the criteria (and while at it, suggest that people with usernames with 'D's and 'M's and 'R's try to perform better … barely on the map!).

[pawanjain]

I am a new member on bitcointalk and I think the code,size and color of the forum are good.
It is my first account here. Meta thread has many good users.I like the merit system and signature and bounty campaign. Many times I received full  btc payment. People want more coin in their crypto wallet so they make more post.  I get time I use bitcoin on blockchain network. I work using miner and I know mining of block.  Now my friend Yang see me and even he need bitcoin and so I told him to create btc address and create account on bitcointalk.

Add my profile url link in your trust list.
------------------------------------------------------------------------------------
@suchmoon I used all the words you described and made a short brief for you  
P.S: Ignore the grammar.

[suchmoon]

My username coincides with the eighth's position best second performing letter, and that’s about it …

I haven’t got my DB handy today, so I can neither confirm nor deny the algorithm, but since you are on my Trust list, I’m ok with trusting the criteria (and while at it, suggest that people with usernames with 'D's and 'M's and 'R's try to perform better … barely on the map!).

As I mentioned to LoyceV, you're earning merits the hard way


Continuing with the supporting data.

The median length of a merit-earning post is 549 characters

Code:

meritdb=# select percentile_disc(0.5) within group (order by length(p."ContentWithoutQuotes"))
from (select sum(m."MeritAmount"), p."PostId", p."ContentWithoutQuotes" from "Posts" p inner join "MeritTxs" m on m."PostId" = p."PostId"
where p."Content" is not null group by p."PostId", p."ContentWithoutQuotes" having sum(m."MeritAmount") >= 0) p;
 percentile_disc
-----------------
             549
(1 row)

For comparison, the average length of a meritorious post is higher, probably skewed by some massive essays. Obviously we're not interested in that.

Code:

meritdb=# select avg(length(p."ContentWithoutQuotes"))
from (select sum(m."MeritAmount"), p."PostId", p."ContentWithoutQuotes" from "Posts" p inner join "MeritTxs" m on m."PostId" = p."PostId"
where p."Content" is not null group by p."PostId", p."ContentWithoutQuotes" having sum(m."MeritAmount") >= 0) p;
          avg
-----------------------
 1445.3326025288816902
(1 row)

top merit-earning words (after removing stop words such as pronouns and conjunctions)

This one is a bit tricky. I use some gnarly code to pre-process posts when I fetch them from Bitcointalk, which includes:

- removing quotes ("ContentWithoutQuotes" in the example above)
- removing punctuation and HTML tags (e.g. smileys)
- removing stop words ("ContentReduced" in the example below).
- some other witchcraft that is not relevant here.

So this is roughly what's happening before the data gets to the database:

Code:

p.ContentReduced = string.Join(" ", p.ContentWithoutPunctuationAndTags.Split(' ').Where(w => !StopWords.Contains(w)));

And then:

Code:

meritdb=# select word, sum("MeritAmount") from (
     select m."MeritAmount", w.word
     from "Posts" p inner join "MeritTxs" m on m."PostId" = p."PostId", unnest(string_to_array(p."ContentReduced", ' ')) w(word)
     where trim(p."ContentReduced") > ''
) g
group by word order by 2 desc limit 100;
    word     |  sum
-------------+--------
 bitcoin     | 322354
 merit       | 307474
 color       | 289022
 member      | 177705
 post        | 160538

This counts all merits of a post towards each word and does it as many times as the word appears in the post. There may be other ways to determine the most "meritorious" words but intuitively this result looks about right.

[LoyceV]

usernames starting with "m" or "s" earned 10 times more merits than those starting with "q" or "u"

Code:

meritdb=# select sum(m."MeritAmount"), substring(u."UserName", 1, 1) from "Users" u inner join "MeritTxs" m on m."ToUserId" = u."UserId"
where substring(u."UserName", 1, 1) > '' group by substring(u."UserName", 1, 1) order by 1 desc;
  sum  | substring
-------+-----------
 17026 | m
 16832 | s
 14134 | a
 13561 | t

[...]

  1427 | q
  1395 | Q
  1357 | u
   944 | U

Triggered Verify, don't trust
I get these numbers, based on last Friday's Merit data dump:

Code:

16879 times m
16701 times s
14034 times a
13405 times t
12982 times B
12864 times T
12757 times b
12346 times L
12008 times c
11810 times S
10759 times C
10444 times D
10079 times A
9063 times d
8919 times H
8828 times p
8257 times M
8063 times k
7533 times P
7036 times g
6701 times j
6582 times r
6282 times R
6155 times J
5568 times h
5547 times e
5531 times n
5367 times K
5231 times f
5052 times i
4828 times G
4665 times l
4389 times E
4357 times V
4255 times o
4177 times F
3924 times v
3909 times N
3479 times x
3153 times w
2850 times I
2707 times z
2626 times y
2565 times W
2464 times O
1543 times Z
1434 times Y
1428 times X
1419 times 1
1413 times q
1381 times Q
1356 times u
942 times U
335 times -
230 times 2
226 times 6
221 times 0
173 times _
172 times 4
162 times 3
105 times #
68 times 7
66 times 8
61 times 5
59 times 9
44 times ~
42 times @
28 times $
25 times .
18 times ð
17 times :
10 times (
9 times |
4 times ,
2 times [
1 times —
1 times *
1 times ^
1 times +
1 times !

Some users may have changed username after I scraped their names, so that could explain the small difference.