List of the top 50-highest day in terms of intra-day merits: . list merit id date dofw day month2 year week month
+-------------------------------------------------------------------------------+ | merit id date dofw day month2 year week month | |-------------------------------------------------------------------------------| 1. | 13018 1 24jan2018 Wednesday 24 1 2018 2018w4 2018m1 | 2. | 6761 2 25jan2018 Thursday 25 1 2018 2018w4 2018m1 | 3. | 4493 3 26jan2018 Friday 26 1 2018 2018w4 2018m1 | 4. | 4192 7 30jan2018 Tuesday 30 1 2018 2018w5 2018m1 | 5. | 3799 6 29jan2018 Monday 29 1 2018 2018w5 2018m1 | |-------------------------------------------------------------------------------| 6. | 3489 4 27jan2018 Saturday 27 1 2018 2018w4 2018m1 | 7. | 3188 5 28jan2018 Sunday 28 1 2018 2018w4 2018m1 | 8. | 2820 8 31jan2018 Wednesday 31 1 2018 2018w5 2018m1 | 9. | 2568 10 02feb2018 Friday 2 2 2018 2018w5 2018m2 | 10. | 2545 9 01feb2018 Thursday 1 2 2018 2018w5 2018m2 | |-------------------------------------------------------------------------------| 11. | 2513 22 14feb2018 Wednesday 14 2 2018 2018w7 2018m2 | 12. | 2463 236 16sep2018 Sunday 16 9 2018 2018w37 2018m9 | 13. | 2308 14 06feb2018 Tuesday 6 2 2018 2018w6 2018m2 | 14. | 2167 12 04feb2018 Sunday 4 2 2018 2018w5 2018m2 | 15. | 2141 15 07feb2018 Wednesday 7 2 2018 2018w6 2018m2 | |-------------------------------------------------------------------------------| 16. | 2141 16 08feb2018 Thursday 8 2 2018 2018w6 2018m2 | 17. | 2077 13 05feb2018 Monday 5 2 2018 2018w6 2018m2 | 18. | 1991 23 15feb2018 Thursday 15 2 2018 2018w7 2018m2 | 19. | 1867 11 03feb2018 Saturday 3 2 2018 2018w5 2018m2 | 20. | 1862 237 17sep2018 Monday 17 9 2018 2018w38 2018m9 | |-------------------------------------------------------------------------------| 21. | 1747 18 10feb2018 Saturday 10 2 2018 2018w6 2018m2 | 22. | 1696 38 02mar2018 Friday 2 3 2018 2018w9 2018m3 | 23. | 1608 25 17feb2018 Saturday 17 2 2018 2018w7 2018m2 | 24. | 1579 21 13feb2018 Tuesday 13 2 2018 2018w7 2018m2 | 25. | 1448 17 09feb2018 Friday 9 2 2018 2018w6 2018m2 | |-------------------------------------------------------------------------------| 26. | 1442 19 11feb2018 Sunday 11 2 2018 2018w6 2018m2 | 27. | 1411 24 16feb2018 Friday 16 2 2018 2018w7 2018m2 | 28. | 1409 32 24feb2018 Saturday 24 2 2018 2018w8 2018m2 | 29. | 1403 27 19feb2018 Monday 19 2 2018 2018w8 2018m2 | 30. | 1382 34 26feb2018 Monday 26 2 2018 2018w9 2018m2 | |-------------------------------------------------------------------------------| 31. | 1354 48 12mar2018 Monday 12 3 2018 2018w11 2018m3 | 32. | 1333 37 01mar2018 Thursday 1 3 2018 2018w9 2018m3 | 33. | 1331 20 12feb2018 Monday 12 2 2018 2018w7 2018m2 | 34. | 1326 35 27feb2018 Tuesday 27 2 2018 2018w9 2018m2 | 35. | 1322 56 20mar2018 Tuesday 20 3 2018 2018w12 2018m3 | |-------------------------------------------------------------------------------| 36. | 1294 238 18sep2018 Tuesday 18 9 2018 2018w38 2018m9 | 37. | 1289 26 18feb2018 Sunday 18 2 2018 2018w7 2018m2 | 38. | 1279 30 22feb2018 Thursday 22 2 2018 2018w8 2018m2 | 39. | 1268 239 19sep2018 Wednesday 19 9 2018 2018w38 2018m9 | 40. | 1266 29 21feb2018 Wednesday 21 2 2018 2018w8 2018m2 | |-------------------------------------------------------------------------------| 41. | 1245 41 05mar2018 Monday 5 3 2018 2018w10 2018m3 | 42. | 1233 68 01apr2018 Sunday 1 4 2018 2018w13 2018m4 | 43. | 1227 57 21mar2018 Wednesday 21 3 2018 2018w12 2018m3 | 44. | 1186 33 25feb2018 Sunday 25 2 2018 2018w8 2018m2 | 45. | 1169 28 20feb2018 Tuesday 20 2 2018 2018w8 2018m2 | |-------------------------------------------------------------------------------| 46. | 1161 351 09jan2019 Wednesday 9 1 2019 2019w2 2019m1 | 47. | 1159 50 14mar2018 Wednesday 14 3 2018 2018w11 2018m3 | 48. | 1146 69 02apr2018 Monday 2 4 2018 2018w14 2018m4 | 49. | 1138 153 25jun2018 Monday 25 6 2018 2018w26 2018m6 | 50. | 1130 51 15mar2018 Thursday 15 3 2018 2018w11 2018m3 | |-------------------------------------------------------------------------------|
List of the top 50-lowest days in terms of intra-day merits: . list merit id date dofw day month2 year week month
+-------------------------------------------------------------------------------+ | merit id date dofw day month2 year week month | |-------------------------------------------------------------------------------| 1. | 312 335 24dec2018 Monday 24 12 2018 2018w52 2018m12 | 2. | 316 333 22dec2018 Saturday 22 12 2018 2018w51 2018m12 | 3. | 325 340 29dec2018 Saturday 29 12 2018 2018w52 2018m12 | 4. | 347 338 27dec2018 Thursday 27 12 2018 2018w52 2018m12 | 5. | 347 298 17nov2018 Saturday 17 11 2018 2018w46 2018m11 | |-------------------------------------------------------------------------------| 6. | 348 304 23nov2018 Friday 23 11 2018 2018w47 2018m11 | 7. | 370 122 25may2018 Friday 25 5 2018 2018w21 2018m5 | 8. | 376 191 02aug2018 Thursday 2 8 2018 2018w31 2018m8 | 9. | 376 342 31dec2018 Monday 31 12 2018 2018w52 2018m12 | 10. | 377 326 15dec2018 Saturday 15 12 2018 2018w50 2018m12 | |-------------------------------------------------------------------------------| 11. | 379 220 31aug2018 Friday 31 8 2018 2018w35 2018m8 | 12. | 383 217 28aug2018 Tuesday 28 8 2018 2018w35 2018m8 | 13. | 385 214 25aug2018 Saturday 25 8 2018 2018w34 2018m8 | 14. | 386 339 28dec2018 Friday 28 12 2018 2018w52 2018m12 | 15. | 389 341 30dec2018 Sunday 30 12 2018 2018w52 2018m12 | |-------------------------------------------------------------------------------| 16. | 394 345 03jan2019 Thursday 3 1 2019 2019w1 2019m1 | 17. | 395 228 08sep2018 Saturday 8 9 2018 2018w36 2018m9 | 18. | 397 320 09dec2018 Sunday 9 12 2018 2018w49 2018m12 | 19. | 399 262 12oct2018 Friday 12 10 2018 2018w41 2018m10 | 20. | 402 329 18dec2018 Tuesday 18 12 2018 2018w51 2018m12 | |-------------------------------------------------------------------------------| 21. | 405 287 06nov2018 Tuesday 6 11 2018 2018w45 2018m11 | 22. | 412 222 02sep2018 Sunday 2 9 2018 2018w35 2018m9 | 23. | 415 278 28oct2018 Sunday 28 10 2018 2018w43 2018m10 | 24. | 415 109 12may2018 Saturday 12 5 2018 2018w19 2018m5 | 25. | 418 186 28jul2018 Saturday 28 7 2018 2018w30 2018m7 | |-------------------------------------------------------------------------------| 26. | 420 187 29jul2018 Sunday 29 7 2018 2018w30 2018m7 | 27. | 421 192 03aug2018 Friday 3 8 2018 2018w31 2018m8 | 28. | 422 140 12jun2018 Tuesday 12 6 2018 2018w24 2018m6 | 29. | 424 276 26oct2018 Friday 26 10 2018 2018w43 2018m10 | 30. | 424 313 02dec2018 Sunday 2 12 2018 2018w48 2018m12 | |-------------------------------------------------------------------------------| 31. | 426 277 27oct2018 Saturday 27 10 2018 2018w43 2018m10 | 32. | 430 264 14oct2018 Sunday 14 10 2018 2018w41 2018m10 | 33. | 430 284 03nov2018 Saturday 3 11 2018 2018w44 2018m11 | 34. | 432 208 19aug2018 Sunday 19 8 2018 2018w33 2018m8 | 35. | 432 221 01sep2018 Saturday 1 9 2018 2018w35 2018m9 | |-------------------------------------------------------------------------------| 36. | 433 282 01nov2018 Thursday 1 11 2018 2018w44 2018m11 | 37. | 435 190 01aug2018 Wednesday 1 8 2018 2018w31 2018m8 | 38. | 435 154 26jun2018 Tuesday 26 6 2018 2018w26 2018m6 | 39. | 444 182 24jul2018 Tuesday 24 7 2018 2018w30 2018m7 | 40. | 445 143 15jun2018 Friday 15 6 2018 2018w24 2018m6 | |-------------------------------------------------------------------------------| 41. | 450 373 31jan2019 Thursday 31 1 2019 2019w5 2019m1 | 42. | 451 206 17aug2018 Friday 17 8 2018 2018w33 2018m8 | 43. | 454 283 02nov2018 Friday 2 11 2018 2018w44 2018m11 | 44. | 455 229 09sep2018 Sunday 9 9 2018 2018w36 2018m9 | 45. | 455 167 09jul2018 Monday 9 7 2018 2018w28 2018m7 | |-------------------------------------------------------------------------------| 46. | 457 216 27aug2018 Monday 27 8 2018 2018w35 2018m8 | 47. | 458 324 13dec2018 Thursday 13 12 2018 2018w50 2018m12 | 48. | 458 227 07sep2018 Friday 7 9 2018 2018w36 2018m9 | 49. | 460 263 13oct2018 Saturday 13 10 2018 2018w41 2018m10 | 50. | 461 130 02jun2018 Saturday 2 6 2018 2018w22 2018m6 | |-------------------------------------------------------------------------------|
During the period from 24/1/2018 to 25/2/2019, the minimum and maximum of intra-day merits are 312 and 13018 , on 24/12/2018 and 24/1/2018, respectively.
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Medians and means of intra-day merits over days of weeks.- In median, the highest days are Monday, Wednesday, and Thursday at 666, 654, and 636, respectively; whislt the lowest days are Friday, Sunday, and Saturday at 554, 607, and 614, respectively. - In means, the highest days are Monday, Wednesday, and both Sunday, Tuesday at 745, 714, and 694, respectively; whilst the lowest days are Friday, Saturday, and Thursday at 614, 627, and 667, respectively. - In both medians and means, Monday is the highest day, whilst the lowest day is Friday. Calendar day is in GMT time.To take away all doubt: the first Merit was this one: 1516831941 1 2818066.msg28853325 35 877396 Use EpochConverter to convert 1516831941 (Unix Time) to GMT: Wednesday 24 January 2018 22:12:21. Basic statistics:. tabstat merit, s(n mean sd p50 p25 p75 min max) format(%9.1f) by(dofw)
Summary for variables: merit by categories of: dofw
dofw | N mean sd p50 p25 p75 min max ----------+-------------------------------------------------------------------------------- Sunday | 53.0 693.7 327.2 607.0 486.0 796.0 389.0 2463.0 Monday | 54.0 744.1 295.2 666.0 562.0 822.0 312.0 1862.0 Tuesday | 53.0 694.0 226.3 626.0 580.0 767.0 383.0 1326.0 Wednesday | 53.0 714.0 217.5 654.0 559.0 759.0 435.0 1268.0 Thursday | 53.0 667.0 220.9 636.0 509.0 764.0 347.0 1333.0 Friday | 53.0 613.7 225.8 554.0 479.0 682.0 348.0 1696.0 Saturday | 53.0 626.8 216.5 614.0 463.0 688.0 316.0 1409.0 ----------+-------------------------------------------------------------------------------- Total | 372.0 679.2 252.4 618.5 518.5 766.5 312.0 2463.0 -------------------------------------------------------------------------------------------
Box plotsOutliers displayed as red circles. Outliers non-displayed.
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Update for 7 weeks after the implementation of Default Trust Change: If nothing new happen next days/ weeks, the delayed effects of Default Trust Change on merit circulations tailed off over the last 7 weeks. If nothing strange occurs, I will stop doing analysis in the topic when the ten weeks later passed (3 more weeks).
Colors: - Red: Decrease- Green: Increase.Two week later: Median: + 37.1Mean: + 24.2Three weeks later: Median: + 15.9Mean: + 15.5Four weeks later: Median: + 15.6Mean: + 11.1Five weeks later: Median: + 6.2Mean: + 6.4Six weeks later: Median: + 4.2Mean: + 3.5 Seven weeks later: Median: + 4.2Mean: + 2.7
More details such as methods of the calculation, can be found there, Tracking the difference of merit circulations with Default Trust Changes
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7 weeks later update:Median: + 4.2 %Mean: + 2.7 %
ABSTRACT(1) Both median and mean of six-week-later period are higher then the before period, with cut-off day is 09/01/2019, at 4.2% and 2.7%, respectively. (2) 50 percent of days in the seven weeks later period have intraday merits in the range from 595 to 736 (the interquartile range), whilst the figures of the before period are 511 to 767. (3) The median of seven-week-later period is almost the same as the figure of the six-week-later period, at 643 and 642.5, respectively.
Box plots:Outliers displayed with red circles Outliers, non-displayed Basic statistics:. tabstat before090119 wkslater_2 wkslater_3 wkslater_4 wkslater_5 wkslater_6 wkslater_7, s(n mean sd p50 p25 p75 min max) format(%9.1f) c(s)
variable | N mean sd p50 p25 p75 min max -------------+-------------------------------------------------------------------------------- before090119 | 324.0 677.0 263.0 616.5 510.5 766.5 312.0 2463.0 wkslater_2 | 14.0 840.4 191.4 845.5 658.0 987.0 611.0 1161.0 wkslater_3 | 21.0 781.9 179.5 715.0 643.0 880.0 587.0 1161.0 wkslater_4 | 28.0 752.0 183.4 713.0 613.5 879.0 450.0 1161.0 wkslater_5 | 35.0 719.5 176.9 655.0 595.0 813.0 450.0 1161.0 wkslater_6 | 42.0 701.0 167.6 642.5 595.0 776.0 450.0 1161.0 wkslater_7 | 49.0 694.9 163.0 643.0 595.0 736.0 450.0 1161.0 ----------------------------------------------------------------------------------------------
Percent changes:. * For Means . di (695-677)*100/677 2.6587888
. * For Medians . di (643-617)*100/617 4.2139384
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sMerits are abundantly everywhere. Someone hold them without any specific purposes. Someone hold them with good purposes, but they have not found merit deserved threads or posts to give their smerits.
In short, I believe that sMerits are not too scarce as most of us imagined, they are abundantly, and need deserved threads or posts to be sent to them. In other words, sMerit is not scarce, whilst the good, merit derserved threads/ posts are really scarce. As for my case, I earned more than 130 merits since December last year, and only fall behind a little bit to the minimum required merits to promote to Senior Member. I will try and believe that I can get promoted till the end of March.
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Update on intra-day merit(from 24/1/2018 to 27/2/2019) Time series plots:Full datasetTruncated dataset: Basic statistics:Full dataset. tabstat merit, s(n mean sd p50 p25 p75 min max)
variable | N mean sd p50 p25 p75 min max -------------+-------------------------------------------------------------------------------- merit | 400 824.725 852.1836 636 525.5 810.5 312 13018 ----------------------------------------------------------------------------------------------
First two days dropped, and last two days dropped (due to incomplete week, 2019w9): . tabstat merit, s(n mean sd p50 p25 p75 min max) format(%9.1f)
variable | N mean sd p50 p25 p75 min max -------------+-------------------------------------------------------------------------------- merit | 396.0 779.9 515.5 634.0 524.0 807.5 312.0 4493.0 ----------------------------------------------------------------------------------------------
Potential outliers: . list id merit date if (merit >= 1232.75 | merit <= 98.75) & merit != .
+-------------------------+ | id merit date | |-------------------------| 1. | 3 4493 26jan2018 | 2. | 4 3489 27jan2018 | 3. | 5 3188 28jan2018 | 4. | 6 3799 29jan2018 | 5. | 7 4192 30jan2018 | |-------------------------| 6. | 8 2820 31jan2018 | 7. | 9 2545 01feb2018 | 8. | 10 2568 02feb2018 | 9. | 11 1867 03feb2018 | 10. | 12 2167 04feb2018 | |-------------------------| 11. | 13 2077 05feb2018 | 12. | 14 2308 06feb2018 | 13. | 15 2141 07feb2018 | 14. | 16 2141 08feb2018 | 15. | 17 1448 09feb2018 | |-------------------------| 16. | 18 1747 10feb2018 | 17. | 19 1442 11feb2018 | 18. | 20 1331 12feb2018 | 19. | 21 1579 13feb2018 | 20. | 22 2513 14feb2018 | |-------------------------| 21. | 23 1991 15feb2018 | 22. | 24 1411 16feb2018 | 23. | 25 1608 17feb2018 | 24. | 26 1289 18feb2018 | 25. | 27 1403 19feb2018 | |-------------------------| 27. | 29 1266 21feb2018 | 28. | 30 1279 22feb2018 | 30. | 32 1409 24feb2018 | 32. | 34 1382 26feb2018 | 33. | 35 1326 27feb2018 | |-------------------------| 35. | 37 1333 01mar2018 | 36. | 38 1696 02mar2018 | 39. | 41 1245 05mar2018 | 46. | 48 1354 12mar2018 | 54. | 56 1322 20mar2018 | |-------------------------| 66. | 68 1233 01apr2018 | 234. | 236 2463 16sep2018 | 235. | 237 1862 17sep2018 | 236. | 238 1294 18sep2018 | 237. | 239 1268 19sep2018 | +-------------------------+
How many outliers identified? . count if (merit >= 1232.75 | merit <= 98.75) & merit != . 40
40 days in total are extremely potential outliers. List of 40 potential outliers, none of them occured in 2019. . list id merit date if (merit >= 1232.75 | merit <= 98.75) & merit != .
+-------------------------+ | id merit date | |-------------------------| 1. | 3 4493 26jan2018 | 2. | 4 3489 27jan2018 | 3. | 5 3188 28jan2018 | 4. | 6 3799 29jan2018 | 5. | 7 4192 30jan2018 | |-------------------------| 6. | 8 2820 31jan2018 | 7. | 9 2545 01feb2018 | 8. | 10 2568 02feb2018 | 9. | 11 1867 03feb2018 | 10. | 12 2167 04feb2018 | |-------------------------| 11. | 13 2077 05feb2018 | 12. | 14 2308 06feb2018 | 13. | 15 2141 07feb2018 | 14. | 16 2141 08feb2018 | 15. | 17 1448 09feb2018 | |-------------------------| 16. | 18 1747 10feb2018 | 17. | 19 1442 11feb2018 | 18. | 20 1331 12feb2018 | 19. | 21 1579 13feb2018 | 20. | 22 2513 14feb2018 | |-------------------------| 21. | 23 1991 15feb2018 | 22. | 24 1411 16feb2018 | 23. | 25 1608 17feb2018 | 24. | 26 1289 18feb2018 | 25. | 27 1403 19feb2018 | |-------------------------| 27. | 29 1266 21feb2018 | 28. | 30 1279 22feb2018 | 30. | 32 1409 24feb2018 | 32. | 34 1382 26feb2018 | 33. | 35 1326 27feb2018 | |-------------------------| 35. | 37 1333 01mar2018 | 36. | 38 1696 02mar2018 | 39. | 41 1245 05mar2018 | 46. | 48 1354 12mar2018 | 54. | 56 1322 20mar2018 | |-------------------------| 66. | 68 1233 01apr2018 | 234. | 236 2463 16sep2018 | 235. | 237 1862 17sep2018 | 236. | 238 1294 18sep2018 | 237. | 239 1268 19sep2018 | +-------------------------+
Truncated dataset. tabstat merit, s(n mean sd p50 p25 p75 min max) format(%9.1f)
variable | N mean sd p50 p25 p75 min max -------------+-------------------------------------------------------------------------------- merit | 372.0 679.2 252.4 618.5 518.5 766.5 312.0 2463.0 ----------------------------------------------------------------------------------------------
Potential outliers: How many potential outliers identified in truncated dataset? . count if (merit >= 1138.5 | merit <= 146.5) & merit != . 22
List of those 22 days . list id merit date if (merit >= 1138.5 | merit <= 146.5) & merit != .
+-------------------------+ | id merit date | |-------------------------| 1. | 27 1403 19feb2018 | 2. | 28 1169 20feb2018 | 3. | 29 1266 21feb2018 | 4. | 30 1279 22feb2018 | 6. | 32 1409 24feb2018 | |-------------------------| 7. | 33 1186 25feb2018 | 8. | 34 1382 26feb2018 | 9. | 35 1326 27feb2018 | 11. | 37 1333 01mar2018 | 12. | 38 1696 02mar2018 | |-------------------------| 15. | 41 1245 05mar2018 | 22. | 48 1354 12mar2018 | 24. | 50 1159 14mar2018 | 30. | 56 1322 20mar2018 | 31. | 57 1227 21mar2018 | |-------------------------| 42. | 68 1233 01apr2018 | 43. | 69 1146 02apr2018 | 210. | 236 2463 16sep2018 | 211. | 237 1862 17sep2018 | 212. | 238 1294 18sep2018 | |-------------------------| 213. | 239 1268 19sep2018 | 325. | 351 1161 09jan2019 | +-------------------------+
Only one of them occured in 2019, on 09/1/2019.
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I thank you, LoyceV, for another data dump this week. Update:Converted intra-day merits in 2019 . list id merit date day month2 year week month dofw if year == 2019
+-----------------------------------------------------------------------------+ | id merit date day month2 year week month dofw | |-----------------------------------------------------------------------------| 343. | 343 603 01jan2019 1 1 2019 2019w1 2019m1 Tuesday | 344. | 344 526 02jan2019 2 1 2019 2019w1 2019m1 Wednesday | 345. | 345 394 03jan2019 3 1 2019 2019w1 2019m1 Thursday | 346. | 346 1082 04jan2019 4 1 2019 2019w1 2019m1 Friday | 347. | 347 835 05jan2019 5 1 2019 2019w1 2019m1 Saturday | |-----------------------------------------------------------------------------| 348. | 348 783 06jan2019 6 1 2019 2019w1 2019m1 Sunday | 349. | 349 570 07jan2019 7 1 2019 2019w1 2019m1 Monday | 350. | 350 782 08jan2019 8 1 2019 2019w2 2019m1 Tuesday | 351. | 351 1161 09jan2019 9 1 2019 2019w2 2019m1 Wednesday | 352. | 352 987 10jan2019 10 1 2019 2019w2 2019m1 Thursday | |-----------------------------------------------------------------------------| 353. | 353 878 11jan2019 11 1 2019 2019w2 2019m1 Friday | 354. | 354 711 12jan2019 12 1 2019 2019w2 2019m1 Saturday | 355. | 355 978 13jan2019 13 1 2019 2019w2 2019m1 Sunday | 356. | 356 1127 14jan2019 14 1 2019 2019w2 2019m1 Monday | 357. | 357 813 15jan2019 15 1 2019 2019w3 2019m1 Tuesday | |-----------------------------------------------------------------------------| 358. | 358 880 16jan2019 16 1 2019 2019w3 2019m1 Wednesday | 359. | 359 1018 17jan2019 17 1 2019 2019w3 2019m1 Thursday | 360. | 360 611 18jan2019 18 1 2019 2019w3 2019m1 Friday | 361. | 361 643 19jan2019 19 1 2019 2019w3 2019m1 Saturday | 362. | 362 658 20jan2019 20 1 2019 2019w3 2019m1 Sunday | |-----------------------------------------------------------------------------| 363. | 363 683 21jan2019 21 1 2019 2019w3 2019m1 Monday | 364. | 364 618 22jan2019 22 1 2019 2019w4 2019m1 Tuesday | 365. | 365 735 23jan2019 23 1 2019 2019w4 2019m1 Wednesday | 366. | 366 715 24jan2019 24 1 2019 2019w4 2019m1 Thursday | 367. | 367 615 25jan2019 25 1 2019 2019w4 2019m1 Friday | |-----------------------------------------------------------------------------| 368. | 368 587 26jan2019 26 1 2019 2019w4 2019m1 Saturday | 369. | 369 655 27jan2019 27 1 2019 2019w4 2019m1 Sunday | 370. | 370 734 28jan2019 28 1 2019 2019w4 2019m1 Monday | 371. | 371 612 29jan2019 29 1 2019 2019w5 2019m1 Tuesday | 372. | 372 510 30jan2019 30 1 2019 2019w5 2019m1 Wednesday | |-----------------------------------------------------------------------------| 373. | 373 450 31jan2019 31 1 2019 2019w5 2019m1 Thursday | 374. | 374 595 01feb2019 1 2 2019 2019w5 2019m2 Friday | 375. | 375 940 02feb2019 2 2 2019 2019w5 2019m2 Saturday | 376. | 376 571 03feb2019 3 2 2019 2019w5 2019m2 Sunday | 377. | 377 796 04feb2019 4 2 2019 2019w5 2019m2 Monday | |-----------------------------------------------------------------------------| 378. | 378 776 05feb2019 5 2 2019 2019w6 2019m2 Tuesday | 379. | 379 559 06feb2019 6 2 2019 2019w6 2019m2 Wednesday | 380. | 380 548 07feb2019 7 2 2019 2019w6 2019m2 Thursday | 381. | 381 611 08feb2019 8 2 2019 2019w6 2019m2 Friday | 382. | 382 623 09feb2019 9 2 2019 2019w6 2019m2 Saturday | |-----------------------------------------------------------------------------| 383. | 383 559 10feb2019 10 2 2019 2019w6 2019m2 Sunday | 384. | 384 642 11feb2019 11 2 2019 2019w6 2019m2 Monday | 385. | 385 585 12feb2019 12 2 2019 2019w7 2019m2 Tuesday | 386. | 386 671 13feb2019 13 2 2019 2019w7 2019m2 Wednesday | 387. | 387 649 14feb2019 14 2 2019 2019w7 2019m2 Thursday | |-----------------------------------------------------------------------------| 388. | 388 607 15feb2019 15 2 2019 2019w7 2019m2 Friday | 389. | 389 523 16feb2019 16 2 2019 2019w7 2019m2 Saturday | 390. | 390 607 17feb2019 17 2 2019 2019w7 2019m2 Sunday | 391. | 391 565 18feb2019 18 2 2019 2019w7 2019m2 Monday | 392. | 392 637 19feb2019 19 2 2019 2019w8 2019m2 Tuesday | |-----------------------------------------------------------------------------| 393. | 393 696 20feb2019 20 2 2019 2019w8 2019m2 Wednesday | 394. | 394 504 21feb2019 21 2 2019 2019w8 2019m2 Thursday | 395. | 395 509 22feb2019 22 2 2019 2019w8 2019m2 Friday | 396. | 396 657 23feb2019 23 2 2019 2019w8 2019m2 Saturday | 397. | 397 608 24feb2019 24 2 2019 2019w8 2019m2 Sunday | |-----------------------------------------------------------------------------| 398. | 398 896 25feb2019 25 2 2019 2019w8 2019m2 Monday | 399. | 399 736 26feb2019 26 2 2019 2019w9 2019m2 Tuesday | 400. | 400 553 27feb2019 27 2 2019 2019w9 2019m2 Wednesday | +-----------------------------------------------------------------------------+
For days in 2018, please get them there
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I would add one more sub-club namely "kissed by Lauda"
LOL, you should create your new own club, not here. Such kind of sub-club as kissed-by-Lauda club will get support from CH, but I don't support it here. It is very distracting from the main purposes of the topic, that is giving list of the top earned-merits profiles and their merited threads. Those cases might be inspirational stories for forum users.
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even when looking at the post history as its usually so short.
There are two possible hypotheses: (1) They are farm accounts. Got promoted from minor merit abusements to move upwards to Junior Member rank. Then, later they got banned due to plagiarism. (2) They are real accounts (not farm ones): But, they simply tried making pseudo- / fake- quality threads to earn at least one merit. Then, later they got banned due to plagiarism.
I don't see reason to sell Junior Member accounts. The most probable scenario is bans due to plagiarism.
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It's a boring club, no girls ![Sad](https://bitcointalk.org/Smileys/default/sad.gif) Haha, it is the right time I raise a big question for you. You and theymos, are one of outstandings in the forum, in aspect of earned-merits. So, earning thousands of merits, for what? It is likely the ever-lasting question, earning or owning too much money for what? ![Roll Eyes](https://bitcointalk.org/Smileys/default/rolleyes.gif)
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I've got you an update. If you get me a list of changes you want (replacing words like Hero Member by Hero for instance), I'll do that for you next time. < ... >
Of course, it is really good if you do it. I believe it is very simple for you, Mr. AI ^^ Replacing those labels is a simple step.
The problem is why I replaced labels is I don't know what happened with table's format. I tried to used different figures of width option, none of them worked, so I adjust those labels shorter a little bit.
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To be honest, as usual, CH makes a very long threads, but I felt really hard to catch his ideas. I appreciated his time to compose those threads, but I strongly think that next time he should make shorter threads that should better concentrate on main ideas.
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I think I have something informative to contribute here For [6] Know the project well before advertising.
I already have a project on that one. Guide on avoid red tags by supporting already known scam projectsIt is very terrible to keep supporting scam projects, especially when DT members or community raised warning or scam accusation everywhere.
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What cause yesterday drops of Gentarium? I felt satisfied with my decision to fastly caught cheap Gentarium yesterday, but I still wanted to know why GTM fell like this. Masternode investors cashed out or something relates to technical aspect of Gentarium platform. I tend to fall into the first theory, masternode investors cashed out.
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As I see, 882 supported newbies are already banned. Those are huge numbers! Now I'm curious who merited most banned Newbies, I'll dig up some data later. Let me guess. Account farmers sent sMerits to Newbies to promote them to Junior Members to join bounties. Due to they are account farmers, they violated forum rules, such as plagiarism, then got banned later.
Of course, we need to look at data-evidence-based statistics. For analysis, before digging deeply, I think you should take a quick analysis on their promoted days. If most of newbies promoted in September last year, there is no reason to dig deeper. I believe most of them promoted and got bans in September last year![Grin](https://bitcointalk.org/Smileys/default/grin.gif)
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I am not sure what happened with zentdex, who published several topics on merit and forum analysis last year. Then, he/ she turned off for months, and come back in last month of 2018. Not sure, why did he/she turned on back, account changed hands, or something different. I guess there are two potential reasons of his ban: - Plagiarism (that I don't think he/ she violated). - Account changed hands. zentdex's BPIP shows Auto Banned. Additionally, zentdex Has at least 48 sMerit available
It is one of very bad ways to destroy sMerits. Am I seeing this right? zentdex has been banned?
Sure, months later you will appear in the list, I believe. I have moved closer to the club of above 250 earned-merits users. As for the OP: now we have another clubs to join, didn't seem like it for I'm a bit short ![Tongue](https://bitcointalk.org/Smileys/default/tongue.gif) ... Might be a good thing if I can see my name on that list haha (jk)
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