[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 |
---|---|---|
59.33 | Isaac (enti)#1546 | for all of the incredibly hard work he has put into the development of our first Grants program. Truly great work. |
53.03 | Isaac (enti)#1546 | amazing work managing and conducting the Grants program products co ordinating with multiple entities |
53.03 | Isaac (enti)#1546 | for leading and managing the grants program with such strength and clarity |
32.33 | GideonRo#3175 | for driving with such grace all the crucial strategy work, the relationships with major stakeholders and the partnership with the TEA. Massive work! |
24.33 | ygg_anderson#4998 | for proactively helping to organize the te study group, creating a one stoo shop and improving our stakeholder reach out list |
23.37 | Isaac (enti)#1546 | for stepping up and leading on both the grants program and redesign of the project management process. Awesome job! |
22.67 | GideonRo#3175 | for taking a well deserved time off and coming back with patience to pick up some of the things that fell while he was away like the cv vote |
21.0 | GideonRo#3175 | for all the guidance and help before going on his retreat. You took on a TON of work before going to make sure all went smooth |
20.25 | Mark D#6686 | for the organization work he is doing with the TE Stakeholder Study data! It's so valuable to have everything on track as we move with the interviews |
20.0 | ygg_anderson#4998 | for rapidily sending out invitations to the stakeholders in his list and for having a great turnout of interviews from the people he invited in our first and second week. |
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 65 praises, 6 (9.23%) 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 65 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.