TOP 120 effective Steemit curators in CN category for the last week (2019.02.18-2019.02.24)

I want to share with you statistics about the most effective Steemit curators in CN 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 CN category took one of the largest part of the reward pool on the last week. So I decided to made a top of the most effective Steemit curators in CN 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	315	1198	2962,35	2,49
2	spanish	556	1220	1461,343	1,228
3	deutsch	216	654	819,861	0,689
4	india	20	52	532,422	0,448
5	cn	92	281	351,855	0,296
6	ita	43	112	296,573	0,249
7	pt	52	148	273,286	0,23
8	tr	50	133	252,449	0,212
9	pakistan	2	4	249,115	0,209
10	polish	89	203	194,758	0,164

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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92 authors published their posts during this week.

2489 accounts participated in the content curating according to information from the database.

13299 votes were made during this week.

351,82 SBD - is the total author rewards for this week.

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TOP-120 effective curators for for the last week

№	Account	Votes	Authors	VAS(%)	Contr. (SBD)	Share %	Eff.
1	@cnbuddy	120	40	19	14,67	4,17	6,38
2	@rivalhw	31	18	76	20,86	5,93	4,08
3	@justyy	84	34	8	7,24	2,06	2,68
4	@steempress-io	28	7	4	22,46	6,38	1,71
5	@partiko	58	28	2	5,53	1,57	1,68
6	@myreader	25	8	19	19,01	5,4	1,65
7	@deanliu	30	7	66	14,85	4,22	1,13
8	@cnstm	60	26	11	3,62	1,03	1,02
9	@team-cn	59	22	38	4,26	1,21	1,02
10	@ace108	40	9	16	6,18	1,76	0,6
11	@abit	20	9	100	5,13	1,46	0,5
12	@rea	21	3	31	10,61	3,02	0,35
13	@lemooljiang	19	9	60	3,34	0,95	0,33
14	@newhope	12	2	29	14,73	4,19	0,32
15	@steem-ua	21	13	2	2,18	0,62	0,31
16	@htliao	19	11	66	2,63	0,75	0,31
17	@alexis555	14	2	27	14,17	4,03	0,31
18	@oflyhigh	16	1	100	23,29	6,62	0,25
19	@magicmonk	17	5	76	4,25	1,21	0,23
20	@julian2013	75	25	26	0,66	0,19	0,18
21	@helene	16	2	100	7,91	2,25	0,17
22	@steemmonsters	10	4	10	3,39	0,96	0,15
23	@xiaohui	16	2	100	6,47	1,84	0,14
24	@slowwalker	6	1	22	11,69	3,32	0,13
25	@thecryptodrive	21	2	20	5,31	1,51	0,12
26	@lebin	34	13	5	0,82	0,23	0,12
27	@angelina6688	27	15	63	0,66	0,19	0,11
28	@bxt	19	5	92	1,96	0,56	0,11
29	@xiguang	21	4	91	2,08	0,59	0,09
30	@onepagex	35	23	7	0,35	0,1	0,09
31	@susanli3769	14	6	100	1,34	0,38	0,09
32	@ericet	37	16	100	0,51	0,14	0,09
33	@bullionstackers	17	9	18	0,86	0,24	0,08
34	@tumutanzi	8	6	38	1,13	0,32	0,07
35	@joythewanderer	9	4	35	1,34	0,38	0,06
36	@wherein	8	5	8	1,1	0,31	0,06
37	@esteemapp	4	3	5	1,93	0,55	0,06
38	@nineteensixteen	60	26	2	0,22	0,06	0,06
39	@fr3eze	19	6	66	0,96	0,27	0,06
40	@jademont	10	3	92	1,86	0,53	0,06
41	@victory622	10	7	77	0,64	0,18	0,05
42	@fishlucy	29	18	50	0,26	0,07	0,05
43	@yellowbird	41	15	65	0,28	0,08	0,05
44	@tvb	22	8	51	0,46	0,13	0,04
45	@chinadaily	16	2	100	1,87	0,53	0,04
46	@mark-waser	16	3	72	1,19	0,34	0,04
47	@ethansteem	16	2	100	1,62	0,46	0,04
48	@jackhircus	14	3	75	1,1	0,31	0,04
49	@dcommerce	7	2	2	1,93	0,55	0,04
50	@curie	4	3	2	1,25	0,36	0,04
51	@steemitboard	24	19	1	0,2	0,06	0,04
52	@accelerator	33	20	1	0,13	0,04	0,03
53	@crypto-report	22	2	90	1,52	0,43	0,03
54	@teamcn-shop	33	23	24	0,13	0,04	0,03
55	@herpetologyguy	16	3	72	0,83	0,24	0,03
56	@lalala	16	2	100	1,41	0,4	0,03
57	@steembasicincome	5	2	75	1,48	0,42	0,03
58	@june0620	10	10	12	0,27	0,08	0,03
59	@honoru	91	32	22	0,09	0,03	0,03
60	@vi1son	11	3	100	0,97	0,28	0,03
61	@redes	3	1	30	2,47	0,7	0,03
62	@dapeng	19	8	100	0,36	0,1	0,03
63	@itchyfeetdonica	14	8	54	0,34	0,1	0,03
64	@sbi5	12	7	19	0,21	0,06	0,02
65	@investmentreport	22	2	90	0,89	0,25	0,02
66	@partiko-promoter	7	7	19	0,24	0,07	0,02
67	@catwomanteresa	17	6	28	0,28	0,08	0,02
68	@coinbaogao	22	1	100	1,6	0,45	0,02
69	@tanlikming	20	15	54	0,11	0,03	0,02
70	@demotruk	2	1	100	2,14	0,61	0,02
71	@windowglass	22	7	39	0,22	0,06	0,02
72	@sbi6	10	7	45	0,29	0,08	0,02
73	@dancingapple	33	10	40	0,15	0,04	0,02
74	@ripperone	2	1	30	1,61	0,46	0,02
75	@blackbunny	16	1	100	1,42	0,4	0,02
76	@hkfund	2	2	88	0,99	0,28	0,02
77	@midnightoil	16	2	100	1,11	0,32	0,02
78	@fundurian	15	6	76	0,31	0,09	0,02
79	@steempress	28	7	4	0,27	0,08	0,02
80	@skenan	14	6	50	0,25	0,07	0,02
81	@davidke20	39	14	23	0,1	0,03	0,02
82	@dclick	1	1	60	2,01	0,57	0,02
83	@cn-malaysia	22	6	47	0,24	0,07	0,02
84	@jincheng	10	8	77	0,1	0,03	0,01
85	@laoyao	16	2	100	0,32	0,09	0,01
86	@coinbitgold	9	2	100	0,28	0,08	0,01
87	@minloulou	21	5	92	0,2	0,06	0,01
88	@reseller	8	3	9	0,35	0,1	0,01
89	@bobdos	18	4	47	0,3	0,09	0,01
90	@cnbuddy-cnstm	60	26	11	0,02	0,01	0,01
91	@fintian	11	6	100	0,1	0,03	0,01
92	@tombstone	4	3	1	0,32	0,09	0,01
93	@qukuailianxuexi	8	2	100	0,4	0,11	0,01
94	@idx	20	9	100	0,14	0,04	0,01
95	@leesongyi	21	1	30	0,84	0,24	0,01
96	@kimxinfo	8	3	100	0,16	0,05	0,01
97	@hendrikdegrote	4	3	2	0,21	0,06	0,01
98	@devsup	7	6	7	0,08	0,02	0,01
99	@sbi7	9	5	54	0,26	0,07	0,01
100	@kadishakho	10	6	100	0,1	0,03	0,01
101	@zhangfapei	8	2	100	0,55	0,16	0,01
102	@eforucom	6	4	4	0,12	0,03	0,01
103	@aellly	13	9	52	0,1	0,03	0,01
104	@winniex	30	9	29	0,15	0,04	0,01
105	@lingfei	16	2	100	0,63	0,18	0,01
106	@slientstorm	11	8	100	0,1	0,03	0,01
107	@chann	51	13	31	0,06	0,02	0,01
108	@pizzapai	18	6	100	0,18	0,05	0,01
109	@abcallen	10	7	71	0,07	0,02	0,01
110	@sweetieprincess	10	5	47	0,17	0,05	0,01
111	@janicechua	19	6	51	0,17	0,05	0,01
112	@sbi2	7	5	9	0,11	0,03	0,01
113	@cornerstone	5	1	30	1,08	0,31	0,01
114	@sbi10	6	6	88	0,09	0,03	0,01
115	@mermaidvampire	7	3	21	0,22	0,06	0,01
116	@exec	16	2	100	0,64	0,18	0,01
117	@jiangchen	23	3	100	0,23	0,07	0,01
118	@arcange	8	2	9	0,38	0,11	0,01
119	@travelgirl	10	5	35	0,24	0,07	0,01
120	@good-karma	4	3	5	0,18	0,05	0,01

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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	@upmewhale	2	2	21	8,22	2,34	0,18
2	@busy.pay	15	7	1	2,03	0,58	0,15
3	@minnowbooster	2	2	60	5,74	1,63	0,12
4	@minnowsupport	15	8	3	0,89	0,25	0,08
5	@merlin7	73	37	0	0,18	0,05	0,07
6	@postpromoter	1	1	59	6,32	1,8	0,07
7	@appreciator	1	1	21	5,32	1,51	0,06
8	@boomerang	1	1	24	2,36	0,67	0,03
9	@minnowvotes	1	1	5	0,83	0,24	0,01

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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.