[nltk_data] Downloading package stopwords to /root/nltk_data... [nltk_data] Unzipping corpora/stopwords.zip.
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 |
|---|---|---|
| 22.25 | enti#1546 | for putting together an overview of options beyond conviction voting for distributing funds for public goods projects in TE |
| 19.0 | kristofer#1475 | for comprehensive answers to my questions about Praise development, and his development work elsewhere in Giveth, helping to bring Praise forward into the public domain, and helping plan and execute for it to be robust and Web 3 operable |
| 15.0 | durgadas#9280 | for his tech decisions around the infrastructure of the Gravity page and course |
| 12.5 | BiancaGadelha#2667 | for considering the Trust document I've started, factors that influence how teams come together and perform in Web 3, https://docs.google.com/document/d/1OTHTFCbBCq6axDlp6qNXShch2e6DM1oLEcLmXzVLhx4/edit?usp=drivesdk , and commenting, looking towards making a publicly available document. |
| 11.75 | innov8tor3#3988 | for being supportive and for stepping in great contributions for Gravity and for sharing his experience around DAOs. You are a valued friend, contributor and coworker for us! |
| 10.5 | Jeremy&TheGospelOfChange#8201 | for considering the Trust document I've started, factors that influence how teams come together and perform in Web 3, https://docs.google.com/document/d/1OTHTFCbBCq6axDlp6qNXShch2e6DM1oLEcLmXzVLhx4/edit?usp=drivesdk , and commenting, looking towards making a publicly available document. |
| 10.5 | Juankbell#7458 | for considering the Trust document I've started, factors that influence how teams come together and perform in Web 3, https://docs.google.com/document/d/1OTHTFCbBCq6axDlp6qNXShch2e6DM1oLEcLmXzVLhx4/edit?usp=drivesdk , and commenting, looking towards making a publicly available document. |
| 9.75 | BiancaGadelha#2667 | for her attentive and supportive care of and onboarding for new folk arriving in TEC and Gravity |
| 9.75 | bear100#9085 | for always resolving my doubts about administration and transparency |
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 9 praises, 0 (0.00%) 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 9 praises, 0 (0.00%) 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.