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Explaining Devtome Earnings

This article explains the Devtome earnings methodologies. It’s a little simplified because a full calculation would require going through every writer and every statistic to demonstrate final results. We’ll go through each column header on a notional Devtome round file, for example devtome_35.csv located here.

To check the calculation scripts for yourself you need to have Python installed, which can be downloaded free from https://www.python.org/ Then save devtome.py from here and edit with IDLE to view code. For reference * means multiply and the order of operators is brackets, exponents (such as 2 squared, 2^2), divide, multiply, add, subtract.

Note: User statistics are available in an easier to view online format here

Explanations

Name
Devtome username

Coin Address
DVC invoice address

Collated Word Count
Words submitted in collated articles

Collated Weighted Word Count
Collated Word Count * 0.3
It’s 0.3 because that’s the relative weighting for collated articles versus original articles.

Image Count
Images submitted in articles

Original Word Count
Words submitted in original articles

Word Count
Collated Word Count + Original Word Count

Weighted Word Count
Collated Word Count + Original Word Count + (Image Count * 10)
Each image counts as 10 words.

Cumulative Payout
Total round shares

Previous Cumulative Payout
Number of shares paid out in previous rounds

Payout
Cumulative Payout - Previous Cumulative Payout

Unique Page Views
Number of page views received that round, data obtained from google analytics after a round ends

Popularity Times Rating
Unique Page Views * Rating Median/99
It’s 99 because that’s the maximum rating.

Advertising Portion
Popularity Times Rating/Total Popularity Times Rating

Advertising Revenue
Advertising Portion * Total Advertising Revenue

Views per Thousand Words
1000 * Unique Page Views/Weighted Word Count

Normalized Popularity
Takes an individual measure of Views per Thousand Words, compares it with the average and deviation from the average Views per Thousand Words to give a comparable measure.

A manual calculation takes several steps and is the same for all normalized measures, the first being to multiply an individual measure by the reciprocal of the average. For anyone who wants to do it for themselves, once you have these numbers:

a. Individual Views per Thousand Words * 1/Average of all Views per Thousand Words (where greater than 0)
b. Calculate 1/Views per Thousand Words for each author (where greater than 0)
c. 0.5/Standard Deviation (all measures of b. above)
Normalized Popularity = a. ^ c.

Rating Median
The median (middle) of all writer’s ratings.

Normalized Rating Median
Takes an individual measure of Rating Median, compares it with the average and deviation from the average rating median to give a comparable measure. The calculation is the same as for Normalized Popularity, but using Rating Median data instead.

Categorized Articles
Total articles that have been categorised

Articles
Total Articles

Categorization
Categorised Articles/Articles

Normalized Categorization
This takes an individual measure of Categorization, compares it with the average and deviation from the average categorization to give a comparable measure. The calculation is the same as for Normalized Popularity, but using Categorization data instead.

Normalized Worth
0.1 * Normalized Categorization + 0.3 * Normalized Popularity + 0.6 * Normalized Rating Median

Earnings Multiplier
This is the result of an iteration that solves for individual payout and multipliers in the context of maintaining the same Total Devtome payout.

Earnings
This multiplies round Payout by Earnings Multiplier, rounded to a whole number.

Worked Example

Using devtome_35.csv. Any small differences are due to rounding, where the Python script generally rounds to three significant figures.

Name
Weisoq

Coin Address
1Cy9e1Yuwboj63XRkMkT6W6YsGDtYDrsUp

Collated Word Count
2735

Collated Weighted Word Count
2735 * 0.3 = 820

Image Count
39

Original Word Count
54623

Word Count
2735 + 54623 = 57358

Weighted Word Count
54623 + 820 + 39 * 10 = 55833

Cumulative Payout
56

Previous Cumulative Payout
55

Payout
56 - 55 = 1

Unique Page Views
314

Popularity Times Rating
314 * 95/99 = 301

Advertising Portion
301/331593 = 0.000908

Advertising Revenue
0.000908 * Total advertising revenue

Views per Thousand Words
1000 * 314/55833 = 5.62

Normalized Popularity
a. 5.62 * (1/9.95) = 0.565
b. Calculate
c. 0.5/standard deviation(b.) = 0.09
Normalized Popularity = 0.565 ^ 0.09 = 0.948

Rating Median
95

Normalized Rating Median
a. 95 * (1/76.1) = 1.248
b. Calculate
c. 0.5/standard deviation(b.) = 2.88
Normalized Popularity = 1.248 ^ 2.88 = 1.9

Categorized Articles
18

Articles
18

Categorization
18/18 = 1

Normalized Categorization
a. 1 * (1/0.913) = 1.095
b. Calculate
c. 0.5/standard deviation(b.) = 2.18
Normalized Popularity = 1.095 ^ 2.18 = 1.22

Normalized Worth
0.1*1.22 + 0.3*0.948 + 0.6*1.9 = 1.54

Earnings Multiplier
MAX(MIN(0.861*1.54,1.4999),0.5001) = 1.33

0.861 is the result of an iteration where individual Normalized Worth measures are applied to all author’s round Payouts, then an overall multiplier is adjusted until the resultant total Earnings is equal to the sum of all Payouts (624 shares). This is therefore applying all respective writer multipliers while keeping the total revenue neutral.

Earnings
1.33 * 1 (rounded to a whole number) = 1


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