TOP 140 effective Steemit curators in Indonesia category for the last week (2018.04.16-2018.04.22)

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

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

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	1368	5677	32794	3,591
2	spanish	2174	4688	11673	1,278
3	cn	308	1296	6730	0,737
4	tr	290	977	6385	0,699
5	deutsch	352	1128	5246	0,574
6	ita	146	393	3496	0,383
7	myanmar	182	539	2757	0,302
8	indonesia	709	1838	2185	0,239
9	japanese	134	496	1924	0,211
10	fr	113	324	1914	0,21
11	pt	101	376	1492	0,163
12	thai	136	441	1341	0,147
13	india	73	141	1321	0,145

You can see here that Indonesia category took one of the largest part of the reward pool on that week. Looks like Indonesia community is one of the biggest and strongest on Steemit. So I decided to made a top of the most effective Steemit curators in Myanmar category.

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.

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.

709 authors published their posts during this week.

8234 accounts participated in the content curating according to information from the database.

34590 votes were made during this week.

2239,19 SBD - is the total author rewards for this week.

TOP-140 effective curators for for the last week

№	Account	Votes	Authors	VAS(%)	Contr. (SBD)	Share %	Eff.
1	@esteemapp	288	187	0	140,83	6,29	37,14
2	@levycore	215	91	12	169,07	7,55	21,7
3	@good-karma	290	187	0	71,97	3,21	18,98
4	@hendrikdegrote	98	59	1	184,03	8,22	15,31
5	@aiqabrago	122	76	26	87,69	3,92	9,4
6	@pharesim	141	91	0	50,81	2,27	6,52
7	@hr1	136	79	0	33,54	1,5	3,74
8	@meerkat	98	59	1	24,09	1,08	2
9	@rok-sivante	36	12	51	112,76	5,04	1,91
10	@curie	98	59	1	20,06	0,9	1,67
11	@thunderbird	98	59	26	15,68	0,7	1,3
12	@razack-pulo	68	45	47	16,16	0,72	1,03
13	@anwenbaumeister	98	59	1	10,98	0,49	0,91
14	@kushed	98	59	1	8,41	0,38	0,7
15	@sndbox	7	4	12	66,72	2,98	0,38
16	@tommyhansen	18	5	38	53,52	2,39	0,38
17	@donkeypong	9	4	9	64,53	2,88	0,36
18	@neoxian	21	9	11	18,86	0,84	0,24
19	@liberosist	98	59	1	2,83	0,13	0,24
20	@slowwalker	9	7	4	23,11	1,03	0,23
21	@lugina	13	4	95	37,61	1,68	0,21
22	@steem-ambassador	8	6	50	19,82	0,89	0,17
23	@paul-gillbanks	29	12	12	8	0,36	0,14
24	@analisa	9	4	9	22,69	1,01	0,13
25	@massivevibration	81	52	5	1,62	0,07	0,12
26	@bullionstackers	25	14	10	5,8	0,26	0,11
27	@abduhawab	29	17	45	4,43	0,2	0,11
28	@candyboy	5	5	7	15,54	0,69	0,11
29	@happyphoenix	51	25	23	2,64	0,12	0,09
30	@acidyo	3	3	10	22,12	0,99	0,09
31	@kpine	2	1	30	65,33	2,92	0,09
32	@kemal13	56	32	34	1,87	0,08	0,08
33	@davidding	3	1	47	56,78	2,54	0,08
34	@dokter-purnama	47	14	90	3,98	0,18	0,08
35	@anomadsoul	3	3	11	16,96	0,76	0,07
36	@kevinwong	9	4	4	11,59	0,52	0,07
37	@thinknzombie	85	56	0	0,85	0,04	0,07
38	@kakilasak	25	18	100	2,34	0,1	0,06
39	@mariska.lubis	42	29	36	1,57	0,07	0,06
40	@jaff	34	15	40	3,07	0,14	0,06
41	@someonewhoisme	2	2	52	16,64	0,74	0,05
42	@ocd	3	3	60	12,81	0,57	0,05
43	@jaki01	3	1	100	34,86	1,56	0,05
44	@ilyasismail	29	18	88	2,01	0,09	0,05
45	@ayijufridar	22	9	97	4,27	0,19	0,05
46	@snowflake	2	2	62	17,77	0,79	0,05
47	@benleemusic	64	42	0	0,63	0,03	0,04
48	@reggaemuffin	1	1	50	26,14	1,17	0,04
49	@dragonpower	16	7	12	3,79	0,17	0,04
50	@doktormuslem	31	10	81	2,61	0,12	0,04
51	@syehlah	46	24	100	0,84	0,04	0,03
52	@albertjester	34	15	100	1,37	0,06	0,03
53	@rizasukma	20	12	98	2,05	0,09	0,03
54	@ettydiallova	29	17	78	1,11	0,05	0,03
55	@freeyourmind	2	2	56	10,92	0,49	0,03
56	@mukhtar.juned	23	10	71	2,24	0,1	0,03
57	@starkerz	6	5	7	4,04	0,18	0,03
58	@bookrak	28	19	100	1,01	0,05	0,03
59	@ezblog	8	2	100	11,85	0,53	0,03
60	@davidorcamuriel	3	1	100	18,43	0,82	0,03
61	@whalepower	49	17	6	0,94	0,04	0,02
62	@baroen96	30	21	60	0,64	0,03	0,02
63	@vesteem	34	22	10	0,67	0,03	0,02
64	@puncakbukit	22	22	8	0,49	0,02	0,02
65	@arie.steem	12	8	92	2,21	0,1	0,02
66	@marketstack	33	22	1	0,61	0,03	0,02
67	@azwarrangkuti	17	3	76	4,58	0,2	0,02
68	@aomura	22	11	17	1,1	0,05	0,02
69	@ihansunrise	36	28	100	0,53	0,02	0,02
70	@rismanrachman	21	14	100	0,84	0,04	0,02
71	@steem.services	17	16	1	0,98	0,04	0,02
72	@zainalbakri	15	9	92	1,85	0,08	0,02
73	@ekavieka	17	10	46	1,64	0,07	0,02
74	@sevenfingers	9	8	38	1,56	0,07	0,02
75	@steemdunk	11	9	11	1,78	0,08	0,02
76	@berkat	34	15	100	0,99	0,04	0,02
77	@thekitchenfairy	22	12	26	1,45	0,06	0,02
78	@halidabahri	45	5	100	1,04	0,05	0,01
79	@nasgu	2	2	86	2,79	0,12	0,01
80	@solidgold	23	15	5	0,34	0,02	0,01
81	@flysky	9	4	6	1,8	0,08	0,01
82	@zamzamiali	27	17	100	0,39	0,02	0,01
83	@playitforward	25	23	2	0,3	0,01	0,01
84	@nyackgrote	31	10	100	0,81	0,04	0,01
85	@riodejaksiuroe	25	13	100	0,33	0,01	0,01
86	@masriadi	50	6	100	1,28	0,06	0,01
87	@acehpungo	22	15	100	0,4	0,02	0,01
88	@boyelleq	38	18	100	0,52	0,02	0,01
89	@kunrishartanto	36	19	100	0,33	0,01	0,01
90	@tusroni	15	9	100	0,45	0,02	0,01
91	@barvon	14	8	87	1,09	0,05	0,01
92	@ezhadolphin	35	23	100	0,34	0,02	0,01
93	@only.home	31	15	100	0,31	0,01	0,01
94	@agusscout	44	17	100	0,34	0,02	0,01
95	@benimardaniat	24	16	100	0,24	0,01	0,01
96	@the-reef	26	13	14	0,51	0,02	0,01
97	@xposed	25	22	10	0,25	0,01	0,01
98	@sireh	42	41	3	0,18	0,01	0,01
99	@rickygunawan	19	6	100	1,11	0,05	0,01
100	@cicisw	23	15	100	0,65	0,03	0,01
101	@rahmanovic	16	10	100	0,61	0,03	0,01
102	@riostarr	13	9	37	0,87	0,04	0,01
103	@amuchtar	17	8	43	1,03	0,05	0,01
104	@dilimunanzar	22	17	100	0,28	0,01	0,01
105	@hansikhouse	7	4	6	1,69	0,08	0,01
106	@zeds	28	15	100	0,44	0,02	0,01
107	@dine77	3	2	83	1,84	0,08	0,01
108	@amre	14	8	100	0,63	0,03	0,01
109	@samymubarraq	32	16	100	0,33	0,01	0,01
110	@eric-boucher	15	14	1	0,35	0,02	0,01
111	@voronoi	5	3	10	1,92	0,09	0,01
112	@domino	1	1	100	4,72	0,21	0,01
113	@irasiregar	32	21	100	0,38	0,02	0,01
114	@roelandp	4	4	1	0,91	0,04	0,01
115	@alhasan	23	11	100	0,53	0,02	0,01
116	@barbro	2	1	78	8,69	0,39	0,01
117	@nadin3	13	5	95	0,72	0,03	0,01
118	@nisarunnisah88	32	18	100	0,33	0,01	0,01
119	@saifuelbahrie	9	3	100	1,24	0,06	0,01
120	@bigram13	2	1	30	4,25	0,19	0,01
121	@seer	1	1	100	4,16	0,19	0,01
122	@steps	2	2	58	1,82	0,08	0,01
123	@abupasi.alachy	30	11	100	0,59	0,03	0,01
124	@dsatria	20	7	100	0,65	0,03	0,01
125	@enlil	1	1	41	6,52	0,29	0,01
126	@cryptos	29	25	5	0,32	0,01	0,01
127	@akmalz	12	9	100	0,43	0,02	0,01
128	@marxause	26	11	100	0,45	0,02	0,01
129	@oemarr	2	2	69	2,69	0,12	0,01
130	@ramta	1	1	10	4,83	0,22	0,01
131	@akbarrafs	22	19	100	0,31	0,01	0,01
132	@bangmimi	30	18	100	0,3	0,01	0,01
133	@cengans	10	9	100	0,59	0,03	0,01
134	@vannour	39	33	1	0,16	0,01	0,01
135	@ghasemkiani	9	9	2	0,8	0,04	0,01
136	@sadramunawar	19	16	100	0,27	0,01	0,01
137	@kaylinart	1	1	100	3,87	0,17	0,01
138	@bahagia-arbi	26	15	100	0,28	0,01	0,01
139	@jseomun	2	2	78	3,14	0,14	0,01
140	@whitneywhitedust	1	1	100	0	0	0

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	@minnowsupport	143	93	0	17,09	0,76	2,24
2	@rocky1	8	5	2	51,64	2,31	0,36
3	@booster	19	10	0	20,29	0,91	0,29
4	@jerrybanfield	10	6	3	23,56	1,05	0,2
5	@mercurybot	21	12	1	9,5	0,42	0,16
6	@boomerang	5	4	5	21,86	0,98	0,12
7	@busy.org	30	14	0	5,67	0,25	0,11
8	@buildawhale	2	2	4	33,25	1,48	0,09
9	@appreciator	3	3	2	20,24	0,9	0,09
10	@sneaky-ninja	6	5	2	6,43	0,29	0,05
11	@upme	2	2	2	13,86	0,62	0,04
12	@ebargains	7	2	23	14,55	0,65	0,04
13	@therising	3	3	3	9,43	0,42	0,04
14	@promobot	2	1	7	19	0,85	0,03
15	@smartsteem	1	1	6	19,91	0,89	0,03
16	@upmewhale	4	4	2	4,61	0,21	0,03
17	@cheetah	48	42	0	0,48	0,02	0,03
18	@speedvoter	36	15	0	1,38	0,06	0,03
19	@passive	14	10	78	1,47	0,07	0,02
20	@estabond	5	4	3	2,93	0,13	0,02
21	@upmyvote	1	1	6	5,02	0,22	0,01
22	@zapzap	10	8	83	0,73	0,03	0,01
23	@steembloggers	4	3	20	2,03	0,09	0,01

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.

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.