TOP 200 effective Steemit curators in KR category for the last week (2018.07.23-2018.07.30)

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

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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Once I have published a post where I made a researsh what categories are most profitable on Steemit.

I showed there that KR category took one of the largest part of the reward pool on that week. So I decided to made a top of the most effective Steemit curators in KR category.

This time I even made a last week rating of the national and language communities included in the TOP-100 categories for total rewards.

№	Category	Authors	Posts	Reward (SBD)	Share %
1	kr	839	3060	9967	2,314
2	spanish	1288	2717	5236	1,216
3	tr	185	495	3471	0,806
4	deutsch	286	860	2851	0,662
5	cn	184	567	1999	0,464
6	japanese	116	348	1744	0,405
7	ita	88	244	1656	0,385
8	pt	91	267	1149	0,267
9	indonesia	337	780	944	0,219
10	polish	175	389	896	0,208
11	india	55	117	894	0,208
12	stemng	22	28	854	0,198
13	fr	78	173	806	0,187
14	japan	22	38	786	0,183

You can find an actual information about TOP 50 categories rewards in this post

The category is a first tag in the post

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.

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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 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 their posts 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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840 authors published their posts during this week.

5857 accounts participated in the content curating according to information from the database.

53451 votes were made during this week.

9984,98 SBD - is the total author rewards for this week.

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TOP-200 effective curators for for the last week

№	Account	Votes	Authors	VAS(%)	Contr. (SBD)	Share %	Eff.
1	@virus707	928	392	2	348,67	3,49	162,71
2	@skan	331	126	8	827,53	8,29	124,13
3	@bramd	150	77	22	449,14	4,5	41,17
4	@songa0906	347	228	13	102,18	1,02	27,73
5	@lucky2	178	110	22	191,95	1,92	25,14
6	@woo7739	111	70	31	206,19	2,07	17,18
7	@lalaflor	194	149	25	81,65	0,82	14,48
8	@centering	147	88	22	138,03	1,38	14,46
9	@fur2002ks	215	110	16	106,01	1,06	13,88
10	@abdullar	92	78	23	135,56	1,36	12,59
11	@ioioioioi	139	97	30	105,39	1,06	12,17
12	@cheongpyeongyull	159	66	23	126,63	1,27	9,95
13	@yungonkim	183	122	18	67,38	0,67	9,79
14	@oldstone	109	61	25	127,24	1,27	9,24
15	@jamieinthedark	257	146	11	51,06	0,51	8,87
16	@hwan100	184	68	23	90,23	0,9	7,3
17	@cjsdns	97	22	62	251,9	2,52	6,6
18	@joceo00	143	37	13	148,46	1,49	6,54
19	@luckystrikes	71	27	53	162,07	1,62	5,21
20	@jjy	119	46	48	83,45	0,84	4,57
21	@leemikyung	75	36	27	104,66	1,05	4,49
22	@hr1	223	141	0	23,72	0,24	3,98
23	@ponzipanda	63	52	39	61,73	0,62	3,82
24	@khaiyoui	120	70	26	43,69	0,44	3,64
25	@gilma	230	106	18	25,58	0,26	3,23
26	@edwardcha888	135	86	27	30,22	0,3	3,09
27	@allsteem	44	26	60	98,09	0,98	3,04
28	@mastertri	138	84	21	30,28	0,3	3,03
29	@gopaxkr	16	16	28	148,83	1,49	2,83
30	@jsj1215	101	50	30	41,39	0,41	2,46
31	@jsquare	75	51	61	40,11	0,4	2,44
32	@momoggo	75	69	21	29,29	0,29	2,41
33	@hjk96	117	67	26	29,84	0,3	2,38
34	@bandabi	45	27	34	73,15	0,73	2,35
35	@seunglimdaddy	178	48	18	40,91	0,41	2,34
36	@twinbraid	78	40	46	48,91	0,49	2,33
37	@allsale	115	46	29	38,73	0,39	2,12
38	@docudai-jun	181	48	38	33,95	0,34	1,94
39	@xinnong	58	43	26	37,55	0,38	1,92
40	@glory7	87	64	37	25,12	0,25	1,91
41	@eunstar	70	25	52	61,07	0,61	1,82
42	@pairplay	65	29	19	51,76	0,52	1,79
43	@wonsama	211	189	20	7,16	0,07	1,61
44	@arama	44	14	100	94,28	0,94	1,57
45	@jingdol	42	19	79	67,16	0,67	1,52
46	@onehand	480	184	7	6,88	0,07	1,51
47	@feyee95	72	57	51	21,47	0,22	1,46
48	@sonki999	110	43	38	28,48	0,29	1,46
49	@jaytop	137	63	23	19,25	0,19	1,44
50	@dodoim	65	15	81	76,89	0,77	1,37
51	@peterchung	63	31	63	36,38	0,36	1,34
52	@bbana	38	19	75	58,82	0,59	1,33
53	@gghite	79	49	41	22,39	0,22	1,31
54	@newiz	112	85	34	12,53	0,13	1,27
55	@changyoon	26	21	100	46,87	0,47	1,17
56	@kilu83	66	48	36	20,38	0,2	1,16
57	@kiwifi	208	102	19	9,21	0,09	1,12
58	@pilotto	26	16	100	58,89	0,59	1,12
59	@wony	30	20	98	45,95	0,46	1,09
60	@sharehows	70	37	29	22,87	0,23	1,01
61	@tasteem	6	6	26	141,06	1,41	1,01
62	@twinpapa	114	51	38	16,49	0,17	1
63	@sitha	69	39	50	20,83	0,21	0,97
64	@haejin	16	12	15	67,13	0,67	0,96
65	@hodolbak	154	83	20	9,44	0,09	0,93
66	@vingroup	60	4	100	190,92	1,91	0,91
67	@ppomppu	57	4	100	183,2	1,83	0,87
68	@bitcoingodperson	67	20	67	36,07	0,36	0,86
69	@vimva	61	49	100	14,48	0,15	0,84
70	@clayop	15	13	100	53,79	0,54	0,83
71	@orange5008	112	59	32	11,86	0,12	0,83
72	@jhy2246	253	69	16	9,59	0,1	0,79
73	@bree1042	125	67	34	9,49	0,1	0,76
74	@muwon123	29	24	89	26,04	0,26	0,74
75	@yoon	48	39	73	15,46	0,15	0,72
76	@emotionalp	98	72	42	7,95	0,08	0,68
77	@m8586	49	31	72	18,2	0,18	0,67
78	@bumblebee2018	80	61	89	8,96	0,09	0,65
79	@leesol	51	45	56	12,06	0,12	0,65
80	@wisdomandjustice	35	27	39	19,67	0,2	0,63
81	@hanwoo	81	36	56	14,7	0,15	0,63
82	@golbang	39	23	38	23,04	0,23	0,63
83	@girina79	82	70	28	7,44	0,07	0,62
84	@fenrir78	51	28	57	18,54	0,19	0,62
85	@steempayco	11	10	90	49,17	0,49	0,59
86	@happyworkingmom	19	16	100	30,07	0,3	0,57
87	@ksc	67	34	51	14,06	0,14	0,57
88	@lovelyyeon	132	51	25	9,37	0,09	0,57
89	@floridasnail	51	29	22	16,17	0,16	0,56
90	@isis-lee	151	99	36	4,7	0,05	0,55
91	@slowwalker	17	6	19	77,28	0,77	0,55
92	@smigol	221	94	15	4,9	0,05	0,55
93	@kyunga	62	49	82	9,48	0,09	0,55
94	@happyberrysboy	46	27	69	16,46	0,16	0,53
95	@shiho	48	31	99	14,43	0,14	0,53
96	@goodhello	69	37	27	11,53	0,12	0,51
97	@katiesa	118	29	42	14,77	0,15	0,51
98	@agawolf	109	70	2	6,05	0,06	0,5
99	@leomichael	28	11	70	37,05	0,37	0,49
100	@neojew	56	25	30	15,95	0,16	0,47
101	@gochuchamchi	45	31	100	12,8	0,13	0,47
102	@eversloth	76	58	36	6,8	0,07	0,47
103	@levoyant	32	24	62	16,29	0,16	0,47
104	@wherever	44	35	100	10,94	0,11	0,46
105	@rideteam	85	48	21	7,86	0,08	0,45
106	@rtytf	37	18	74	20,64	0,21	0,44
107	@armdown	28	18	82	20,02	0,2	0,43
108	@danbain	27	14	91	25,61	0,26	0,43
109	@morning	23	16	51	22,78	0,23	0,43
110	@kwonjs77	95	11	97	33,16	0,33	0,43
111	@tata1	37	26	64	13,53	0,14	0,42
112	@lesto	78	55	36	6,46	0,06	0,42
113	@tailcock	106	60	39	5,81	0,06	0,42
114	@olorin	20	10	100	35,39	0,35	0,42
115	@ssm1810	12	9	100	38,59	0,39	0,41
116	@himapan	71	48	34	7,17	0,07	0,41
117	@kmlee	54	39	43	8,71	0,09	0,4
118	@steemitjp	60	22	27	14,7	0,15	0,38
119	@kibumh	131	41	38	7,51	0,08	0,37
120	@songvely	91	48	40	6,43	0,06	0,37
121	@leesongyi	37	26	86	11,6	0,12	0,36
122	@minyool	36	11	90	27,01	0,27	0,35
123	@yangpankil27	53	41	38	7,2	0,07	0,35
124	@hansangyou	61	26	35	11,33	0,11	0,35
125	@sinner264	52	23	73	12,32	0,12	0,34
126	@romi	37	24	74	11,75	0,12	0,34
127	@dayul	47	27	52	10,43	0,1	0,34
128	@sunsu	111	69	32	4,08	0,04	0,34
129	@mircokim22	37	37	100	7,79	0,08	0,34
130	@pppnim	94	52	40	5,19	0,05	0,32
131	@okja	55	26	59	10,03	0,1	0,31
132	@carrotcake	56	49	67	5,33	0,05	0,31
133	@skuld2000	69	40	46	6,38	0,06	0,3
134	@tradingideas	38	31	66	7,95	0,08	0,29
135	@jinuking	59	46	100	5,25	0,05	0,29
136	@eesa224	33	19	51	12,78	0,13	0,29
137	@joeypark	23	22	91	11,16	0,11	0,29
138	@hyokhyok	63	39	25	6,15	0,06	0,29
139	@rosaria	48	32	54	7,37	0,07	0,28
140	@stimcity	16	7	100	33,72	0,34	0,28
141	@ramengirl	14	12	100	19,87	0,2	0,28
142	@xxnoaxx	143	96	19	2,49	0,02	0,28
143	@sadmt	88	35	38	6,82	0,07	0,28
144	@ddllddll	74	40	76	5,61	0,06	0,27
145	@rayheyna	56	23	74	10	0,1	0,27
146	@roychoi	32	12	45	18,93	0,19	0,27
147	@kyju	91	56	28	3,93	0,04	0,26
148	@freegon	82	51	47	4,32	0,04	0,26
149	@tasquai	54	13	99	16,62	0,17	0,26
150	@yann03	38	31	73	6,7	0,07	0,25
151	@cheolwoo-kim	40	13	88	15,64	0,16	0,24
152	@ballantines30	80	28	46	7,35	0,07	0,24
153	@zzings	23	16	64	11,83	0,12	0,23
154	@autokjk70	89	53	50	3,67	0,04	0,23
155	@twohs	41	29	74	6,55	0,07	0,23
156	@hooo	57	21	98	9,05	0,09	0,23
157	@donquixote17	19	12	100	14,5	0,15	0,21
158	@dmsqlc0303	55	42	31	3,99	0,04	0,2
159	@granturismo	17	13	100	12,68	0,13	0,2
160	@l-s-h	34	4	96	40,17	0,4	0,19
161	@funfund	38	11	51	14,57	0,15	0,19
162	@greenlatte	61	34	33	4,71	0,05	0,19
163	@jjjjabe	42	32	69	4,87	0,05	0,19
164	@holic7	15	11	58	14,16	0,14	0,19
165	@sndbox	7	7	15	21,88	0,22	0,18
166	@innovit	23	21	85	7,12	0,07	0,18
167	@nomader	72	55	70	2,74	0,03	0,18
168	@crowsaint	60	54	54	2,73	0,03	0,18
169	@joeuhw	31	7	100	21,89	0,22	0,18
170	@stellasjshin	19	12	36	12,35	0,12	0,18
171	@thelump	45	40	90	3,57	0,04	0,17
172	@hersnz	67	41	33	3,45	0,03	0,17
173	@bookkeeper	64	52	71	2,72	0,03	0,17
174	@kyle-event	32	11	95	13,04	0,13	0,17
175	@uksama	72	57	49	2,45	0,02	0,17
176	@newage92	48	43	75	3,37	0,03	0,17
177	@jhparksy	56	23	100	6,14	0,06	0,17
178	@isi3	64	43	30	3,27	0,03	0,17
179	@woolnami	31	12	80	10,96	0,11	0,16
180	@junny	93	53	30	2,48	0,02	0,16
181	@rebok7856	122	52	49	2,57	0,03	0,16
182	@rt4u	54	48	30	2,73	0,03	0,16
183	@epitt925	65	43	41	3	0,03	0,15
184	@noisysky	123	96	24	1,29	0,01	0,15
185	@abcteacher	24	18	86	6,91	0,07	0,15
186	@sd974201	425	213	9	0,6	0,01	0,15
187	@parkname	69	39	58	3,29	0,03	0,15
188	@warofcraft	58	29	20	4,31	0,04	0,15
189	@soosoo	53	16	57	7,92	0,08	0,15
190	@dj-on-steem	120	57	40	2,22	0,02	0,15
191	@yuky	26	16	100	7,2	0,07	0,14
192	@fabien	6	5	100	23,65	0,24	0,14
193	@ssin	27	17	6	6,82	0,07	0,14
194	@kimkwanghwa	97	39	34	2,83	0,03	0,13
195	@kimegggg	49	30	82	3,65	0,04	0,13
196	@cine	83	38	35	2,93	0,03	0,13
197	@lighthil	11	10	100	10,82	0,11	0,13
198	@lager68	73	33	77	3,29	0,03	0,13
199	@ab7b13	58	38	95	2,95	0,03	0,13
200	@shinternational	88	9	65	11,15	0,11	0,12

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I took all vote bots (most of them are working like pay for vote) in the separate table. Because we can't call them effective curators. Their work depends on authors payments and activity.
If you know another bots in the list above please tell me about it.

№	Account	Votes	Authors	VAS(%)	Contr. (SBD)	Share %	Eff.
1	@busy.pay	420	153	3	256,52	2,57	46,72
2	@smartsteem	6	4	4	69,2	0,69	0,33
3	@busy.org	166	70	1	3,42	0,03	0,29

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Now you know all these heroes. Their daily work gives hope to some authors, and some even a decent income. Their work attracts new authors in Steemit.

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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.