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User's sMerit Network size ? Data to select possible Merit Sources
1. Introduction

We?ve seen various post related to the Merit Network, both from a user?s perpective (Our very own sMerit Network Picture) and from a global perspective (sncc's Merit network analysis: merit rank distribution and satellites).
The question of how to derive the potential sMerit Sources has come up recurrently, so I thought about digging into the data to see how this could be determined, or at least eased.
The basic principal that I?m using is that potential users should have a track of sMerit awarding in their history. I think that the best criteria is determined by the size of the personal outgoing sMerit Network. That is, the number of distinct users that a certain user has awarded with sMerit over time.
The hypothesis behind is that the more users that one has merited, the better knowledge he has of the underlying principles. The amount awarded is secondary in this case, but also a factor to narrow down candidates.

This can be done from:
a)   A Global perspective: Aggregating all the data for a given user.
b)   A Section/Subsection perspective: Aggregating the data for a given user in a specific section/subsection.

The numbers presented are those that I found, based on the snapshot of data collected 10 days ago (and aligned with the data presented in Forum Metrics - Section/subsection sMerit breakdown.). Since I do not know who the exact 79 sMerit Sources are, I have not taken them off the analysis. Logically, the current sMerit Sources should come up in the data right at the top in most cases.
In addition to determining potential candidates for Merit Sources based on the above criteria, Merit Sources could be added by including moderators to that role, since they are already scouting the forum and parsing posts daily. It depends on whether they consider they can perform this additional task along side current tasks. This idea was nicely suggested by seoincorporation in other posts.

In all cases, the candidates need to be manually screened, and vetoed if necessary (tracking DT, checking merited posts, etc.).

In addition, I?d like to mention that determining the potential sMerit Sources comes in second place to determining where these sMerit Sources should develop their activity. Determining where there is a lack of sMerit Sources, in my opinion, derives from knowing how much sMerit is being given in a given section/subsection, and getting a measure of how many posts go unmerited, all in a given timeframe. The deficit can then covered by placing sMerit sources at work in those areas.

The idea here is to be able to detect potential sMerit Source candidates, not to determine in this exercise where exactly they need to be active since that requires other input variables like I said.

2. Global Perspective
From a global perspective, this is the distribution of the size of the outgoing sMerit Network for all users with at least 1 sMerit sent over their history:

We can see that 26 people have sent sMerit to over 100 distinct users each, 4 people to between 90 and 100 users, and so on.
Only 6,63% of the users have a network with 10 or more awarded users.
On the other extreme, a mass of 7.335 people have sent sMerit to only one user, representing 54,61% of all total sMerit awarders.

I think that this last data is a low key tone in the system (more than half of awarders only awarded one user). Obviously this is related to the amount of sMerit available, but from the big picture?s point of view it doesn?t look great.

So from a global point of view, the users that are candidates to being sMerit Sources would be (again, sMerit Sources will probably be on the lists at the top):
(note: user with an sMerit network of 30 and above are provided in this list. Full list in a more user friendly format can be retrieved here:Google Drive sMerit Outgoing Network 20180516)

The idea would be to scout the users on the list in a top down manner, favouring network size, but also using the complementary provided fields as filter criteria. Provided columns are:
User_from: User_id
Name: User alias
Rank: User rank (as of data extraction)
nSentTo: Network size. Number of distinct users that user_from has sent sMerit to.
sMeritSent: aggregate sMerit sent by the user.
nTx: Number of sMerit Transactions.
avgSent: Average sMerit sent per Transaction.
stdDevSent: Standard Deviation of sent sMerits.
cVarSent: Coefficient of Variation (the smaller, the more constant value of merit awarded by the user)


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