[nltk_data] Downloading package stopwords to /root/nltk_data... [nltk_data] Package stopwords is already up-to-date!
This document processes the outputs of the praise reward system and performs an analysis of the resulting token reward distribution.
Since praise gets valued on a scale, we can take a look at how often each value of the scale gets assigned by quantifiers. Note: This metric disregards scores of praise marked as a duplicate, since the score of the original is already being taken into account.
The ten highest rated contributions for this round were the following:
| Avg. score | To | Reason |
|---|---|---|
| 114.33 | mateodaza#3156 | @MoeNick, for their incredible work making the IO Dapp ready for launch. It went so swimmingly and you guys really rocked it in the last few weeks, the change of direction was scary honestly... i didn't think we had enough time, but you guys really knocked it out of the park, got it ready EARLY and were here to help out on anything else! Incredible! |
| 114.33 | mateodaza#3156 | @CarlosQ, , for getting an extra ~800 verified projects on the platform right before launch ROCKSTARS!!!! |
| 98.67 | Griff (💜,💜)#8888 | for being such a great mentor - I never stop learning new skills and gaining confidence |
| 98.67 | Griff (💜,💜)#8888 | for his vision and drafting the system, creating the narratives and assembling the team that got us to where we are now |
| 96.0 | mohammad_ranjbar_z#2709 | for working together on the GIVeconomy and making the most amazingly ridiculous (in a good way) amount of dev progress this week - I'm in AWE |
| 96.0 | mohammad_ranjbar_z#2709 | @MoeNick, for their incredible work making the IO Dapp ready for launch. It went so swimmingly and you guys really rocked it in the last few weeks, the change of direction was scary honestly... i didn't think we had enough time, but you guys really knocked it out of the park, got it ready EARLY and were here to help out on anything else! Incredible! |
| 89.0 | paxthemax#4454 | for being a great team of developers and preparing giveth.io and the GIVeconomy for the next phase |
| 89.0 | willyfox#1178 | for being an awesome, hardworking, loving, vibes are high giveth community ❤️❤️❤️❤️ |
| 89.0 | willyfox#1178 | for always being around when needed and supporting Giveth. |
| 82.5 | willyfox#1178 | for moving things forward and working on zapper even when he has covid! What a champ he is!! ❤️ |
We can now take a look at the distribution of the received praise rewards. You can toggle the inclusion of the different sources by clicking on the legend.
We can also take a look at the amount of praise different users gave.
Now for something more fun: let's surface the top "praise flows" from the data. Thanks to @inventandchill for this awesome visualization! On one side we have the top 15 praise givers separately, on the other the top 25 receivers. The people outside the selection get aggregated into the "REST FROM" and "REST TO" categories.
Now let's take a closer look at the quantification process and the quantifiers:
To aid the revision process, we highlight disagreements between quantifiers.
This graphic visualizes controversial praise ratings by sorting them by the "spread" between the highest and lowest received score.
Please keep in mind that this is a visual aid. If there are several praise instances with similar spread and quant score, all but one end up "hidden" on the chart. For an exhaustive list, take a look at the exported file "praise_outliers.csv" .
Let's see how different quantifiers behaved by showing the range of praise scores they gave.
To interpret the box plot:
Bottom horizontal line of box plot is minimum value
First horizontal line of rectangle shape of box plot is First quartile or 25%
Second horizontal line of rectangle shape of box plot is Second quartile or 50% or median.
Third horizontal line of rectangle shape of box plot is third quartile or 75%
Top horizontal line of rectangle shape of box plot is maximum value.
Among 1356 praises, 526 (38.79%) do not agree on duplication
Praise instances with disagreements in duplication are collected in 'results/duplication_examination.csv'. To compare, look at the last 4 columns: 'DUPLICATE MSG 1/2/3' and 'ORIGINAL MSG'.
Among 1356 praises, 28 (2.06%) do not agree on dismissal
Praise instances with disagreements in dismissal are collected in'results/dismissal_disaggreed.csv'. You can further look into who dismissed and who did not.