[nltk_data] Downloading package stopwords to /home/mitch/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 |
---|---|---|
67.33 | mateodaza#3156 | for all the work during the summer on the abc advance page |
42.0 | kristofer#1475 | for his demo today showing the latest features in the praise dashboard, including in app analytics, new export methods and built in distribution file exports! |
42.0 | r-x-x#8344 | for being super helpful crafting the API queries for the advanced ABC page! |
39.25 | r-x-x#8344 | for all the analysis work he's done for the TEC! It's very important and often goes unnoticed |
30.25 | pat.zip (TE Academy)#5266 | for all the work they're doing at the TEA <3 I'm really excited about the Fundamentals course! |
26.75 | kristofer#1475 | for joining the rewards wg call and taking on compiling all the data for sending out missing rewards to contributors |
24.33 | acidlazzer#5796 | for designing the beautiful promo image we used for our Twitter Space event |
23.5 | Contessa#6497 | For their impact on Gravity in multiple ways, either creating and publishing content, supporting coordination, taking cases, making twitter spaces, working on website and narrative, raising awareness, giving advice processes, leading by example, giving ideas and just being an amazing network of people for this project to continue growing. |
23.5 | enti#1546 | for hosting the first Token Engineering twitter space in spanish and share about it with the spanish speaker community 💖💖 |
23.0 | BiancaGadelha#2667 | For their impact on Gravity in multiple ways, either creating and publishing content, supporting coordination, taking cases, making twitter spaces, working on website and narrative, raising awareness, giving advice processes, leading by example, giving ideas and just being an amazing network of people for this project to continue growing. |
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 176 praises, 29 (16.48%) 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 176 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.