TOP 100 effective Steemit сurators that encourage discussion for the 2017.10.20

I want to share with you statistics about the most effective Steemit curators.

This statistic is not about how much the authors or curators have earned. This statistics shows the list of curators, whose contribution to the reward pool distribution is the most significant.

image source

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What does this mean?

You can say that there is nothing interesting in this statistics. That it is clear that the reward pool is distributed by whales. But!

The most interesting thing is how the curator distributes the reward pool. He can vote only for his posts and his comments. He can vote for a selected circle of authors and affiliated accounts. But also he can vote for a large number of authors who publish interesting content.

Thus, an effective curator is a curator who has sufficient Steem Power (he can be an investor or a popular author who has earned his Steem Power by publishing interesting content), devoting time and effort to the content curating at Steemit and distributing a reward pool in favor of the authors. And the efficiency level is estimated by how much SBD curator distributes among as many authors as possible.

But this time we will review those curators who reward the discussions, that is, they vote for the comments of other users.

According to the ideology of the Steemit creators, the discussion is as valuable an element as the author's content. Confirmation of this is the allocation of a separate pool of awards for comments.

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How it works?

Votes - Each curator distributes a certain part of the reward pool with his votes (upvote / flag).

Authors - This part of the pool he distributes between a certain number of authors.

VAS (vote average strength) - For general awareness, we can estimate the average vote strength in percents (%), with which the curator votes.

Contr. (SBD) (Contribution in SBD) - The distributed part of the pool is the contribution of the curator, it is calculated in SBD. In this case, the author's reward is taken into account. The curator's reward is not taken into account.

Share % - The percentage of the of the curator contribution among the contributions of all curators, we can also estimate for information purposes in %.

Eff. - The effectiveness of the curator is estimated in conventional units and is calculated as follows.

The total number of authors who published rewarded comments for the period under study is determined.
Then the contribution of the curator is divided by the total number of authors, and then multiplied by the number of authors for whom the curator voted for the period.

Thus, we see that, having distributed even a smaller number of SBD between a larger number of authors, the curator can be more effective than other curators. At the same time, having a greater voice power, but not actively voting, supporting a small number of authors, the curator takes a lower position in the rating.

And now, statistics.

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3537 authors published their rewarded comments during this day.

3613 accounts participated in the comments curating according to information from the database.

18508 votes were made during this day.

1925,57 SBD - is the total author rewards for this day.

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Given the number of curators supporting the comments and influencing their reward, I decided to reduce the number of curators in this toplist.

TOP-100 effective comments curators for October 20, 2017 (24 Hours period)

№	Account	Votes	Authors	VAS(%)	Contr. (SBD)	Share %	Eff.
1	@good-karma	351	266	0	84,43	4,38	6,35
2	@thing-2	60	56	100	31	1,61	0,49
3	@gentlebot	60	56	100	31,04	1,61	0,49
4	@pharesim	83	56	0	20,75	1,08	0,33
5	@esteemapp	340	260	1	3,4	0,18	0,25
6	@jaki01	38	35	10	21,88	1,14	0,22
7	@bitcoiner	302	243	1	3,03	0,16	0,21
8	@surpassinggoogle	33	30	1	16,83	0,87	0,14
9	@apink	32	15	29	20,19	1,05	0,09
10	@exyle	30	26	4	10,54	0,55	0,08
11	@derrick829	46	8	60	35,38	1,84	0,08
12	@djohan	80	28	51	10,16	0,53	0,08
13	@feruz	348	266	1	1,07	0,06	0,08
14	@papa-pepper	46	41	13	6,02	0,31	0,07
15	@mattclarke	19	17	64	15,5	0,8	0,07
16	@elyaque	82	49	8	4,1	0,21	0,06
17	@amiramnoam	19	10	62	16,22	0,84	0,05
18	@lexiconical	21	17	10	7,63	0,4	0,04
19	@gamer00	39	22	13	6,89	0,36	0,04
20	@saramiller	32	9	27	17,66	0,92	0,04
21	@gardenofeden	31	9	18	15,04	0,78	0,04
22	@floridasnail	39	29	10	4,37	0,23	0,04
23	@eric-boucher	42	14	21	8,93	0,46	0,04
24	@blocktrades	3	3	5	33,49	1,74	0,03
25	@enomujjass	24	16	16	6,75	0,35	0,03
26	@tommyhansen	12	7	52	15,88	0,82	0,03
27	@ats-david	10	10	3	8,89	0,46	0,03
28	@dennisschroeder	25	17	100	5,94	0,31	0,03
29	@zer0hedge	15	10	96	8,93	0,46	0,03
30	@adm	175	1	2	115,71	6,01	0,03
31	@steevc	62	54	3	1,18	0,06	0,02
32	@johnsmith	6	3	100	21,71	1,13	0,02
33	@lordoftruth	30	22	2	3,45	0,18	0,02
34	@czechglobalhosts	17	14	2	4,16	0,22	0,02
35	@everlove	35	14	13	5,44	0,28	0,02
36	@lyndsaybowes	22	19	7	4,34	0,23	0,02
37	@mammasitta	22	13	29	6,02	0,31	0,02
38	@alexbeyman	23	20	20	3,92	0,2	0,02
39	@teamsteem	11	9	1	5,99	0,31	0,02
40	@juliank	29	25	1	3,19	0,17	0,02
41	@stellabelle	4	3	55	22,65	1,18	0,02
42	@asmolokalo	12	6	53	10,38	0,54	0,02
43	@quinneaker	28	16	10	4,55	0,24	0,02
44	@adsactly	7	6	2	9,62	0,5	0,02
45	@transisto	3	2	34	27,8	1,44	0,02
46	@rcarter.witness	15	14	18	5,32	0,28	0,02
47	@doitvoluntarily	18	17	16	1,69	0,09	0,01
48	@lichtblick	29	27	1	0,73	0,04	0,01
49	@whalecurry	14	3	100	12,16	0,63	0,01
50	@arturomdg	11	1	100	38,22	1,98	0,01
51	@centering	9	7	20	4,39	0,23	0,01
52	@elewarne	11	8	100	2,52	0,13	0,01
53	@ackza	23	22	34	1,47	0,08	0,01
54	@ghasemkiani	7	6	29	5,93	0,31	0,01
55	@ulfr	16	9	44	5,57	0,29	0,01
56	@maryfavour	10	6	32	7,23	0,38	0,01
57	@extrospect	5	1	100	51,82	2,69	0,01
58	@aaronkoenig	20	17	100	1,09	0,06	0,01
59	@deanliu	7	4	73	11,86	0,62	0,01
60	@happymoneyman	16	11	22	3,69	0,19	0,01
61	@zoethehedgehog	12	8	100	2,64	0,14	0,01
62	@kaylinart	19	16	2	1,93	0,1	0,01
63	@xiknybuc	8	2	100	21,18	1,1	0,01
64	@raybrockman	11	10	23	4,54	0,24	0,01
65	@enginewitty	42	20	11	0,93	0,05	0,01
66	@htliao	6	6	1	3,06	0,16	0,01
67	@double-u	15	8	68	5,15	0,27	0,01
68	@goldmatters	4	3	100	6,66	0,35	0,01
69	@xpilar	24	11	3	2,25	0,12	0,01
70	@jwolf	19	15	2	1,58	0,08	0,01
71	@fur2002ks	29	26	20	1,52	0,08	0,01
72	@surfermarly	8	8	48	3,68	0,19	0,01
73	@staticinstance	8	7	13	5,34	0,28	0,01
74	@kevinwong	2	2	54	13,04	0,68	0,01
75	@tt-dogg	55	13	100	1,67	0,09	0,01
76	@jiahn	64	27	30	1,65	0,09	0,01
77	@hooshang	16	2	100	10,66	0,55	0,01
78	@jerrybanfield	7	7	6	2,63	0,14	0,01
79	@thedamus	28	10	40	4,1	0,21	0,01
80	@sochul	4	4	48	5,25	0,27	0,01
81	@apolymask	12	10	100	2,06	0,11	0,01
82	@flameburst	6	2	100	8,86	0,46	0,01
83	@bitcoincompany	5	2	100	13,48	0,7	0,01
84	@meesterboom	52	29	1	1,25	0,06	0,01
85	@richq11	36	23	10	1,8	0,09	0,01
86	@barbro	3	3	100	6,14	0,32	0,01
87	@whatsup	45	33	1	0,59	0,03	0,01
88	@nanzo-scoop	5	5	8	4,8	0,25	0,01
89	@inventor16	6	6	12	3,69	0,19	0,01
90	@tipu	65	23	14	1,1	0,06	0,01
91	@daveks	42	37	1	1,2	0,06	0,01
92	@little-peppers	42	37	14	1,07	0,06	0,01
93	@canadian-coconut	6	6	2	4,79	0,25	0,01
94	@abh12345	32	25	6	0,76	0,04	0,01
95	@ctrl-alt-nwo	14	14	1	1,4	0,07	0,01
96	@ozhiya	8	6	22	3,57	0,19	0,01
97	@kafkanarchy84	13	13	11	1,98	0,1	0,01
98	@stackin	32	31	1	1,62	0,08	0,01
99	@humanearl	6	4	100	9,11	0,47	0,01
100	@steemcleaners	1	1	28	22,03	1,14	0,01

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Now you know all these heroes. Their daily work increases the interest in the discussion, gives hope to some authors, and some even a decent income. Their work attracts new authors in Steemit and makes existing users remain.

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Information sources

All information is prepared by querying data from a SteemSQL - SQL database containing information from Steem's blockchain, as well as by calculations based on this data.

Special thanks to @arcange for SteemSQL and for the advice provided to me during the development of this project.