[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 |
|---|---|---|
| 78.5 | r-x-x#8344 | for doing a massive amount of work to move our Dune dashboard over to the latest version fo Dune. This entailed rewriting of a large number of queries. He also did a nice refactoring of the UI to make our analytics much easier to understand. Quantifiers: this was a lot of work. Please quantify accordingly. |
| 27.5 | acidlazzer#5796 | for designing TEC traits for Public Nouns, loving them! |
| 23.5 | r-x-x#8344 | for securing admin access to the TEC's account on LinkedIn and doing a little cleanup there. |
| 22.25 | enti#1546 | for doing an amazing job leading the TEA Latam study group! I hear nothing but high praise from my latam circle about his consistency and quality. Thanks so much for your great work, passing the praise along :) |
| 17.0 | BiancaGadelha#2667 | for always listening, always being supportive, always willing to offer suggestions, and for practical suggestions that have targeted meaning and value. She's a great example to many in Discord and DAOs in general. Gravity and Gravitons have a lot to offer in such settings. |
| 17.0 | GideonRo#3175 | for stepping up into support roles for folk enquiring in the #💬｜general channel, because it's such an important first step for folks arriving and seeking direction and knowledge. Thank you. |
| 17.0 | natesuits#4789 | for stepping up into support roles for folk enquiring in the #💬｜general channel, because it's such an important first step for folks arriving and seeking direction and knowledge. Thank you. |
| 15.0 | Marathonmind#3078 | for the nice work and commitment making the curation service threads for twitter! |
| 12.4 | acidlazzer#5796 | for designing this really cool quantifier robot themed Noun avatar! |
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, 1 (11.11%) 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.