Introduction

This study explores the distribution of thanks. The first figure presents data on the number of thanks the average person receives. The second figure presents data on whether thanks are received evenly throughout the year or in clusters.

SQL Query

use PROJECT;

select B.user_editcount as Edit_Count, A.log_title as User_Name, A.log_timestamp as Thank_Time

from (select log_title, log_timestamp from logging_userindex where (log_action = 'thank' and log_type='thanks' and log_timestamp < timestamp(TIME1) and log_timestamp >= timestamp(TIME2))) as A

join (select user_editcount, user_name from user) as B

on A.log_title = B.user_name order by B.user_editcount, A.log_title

-- For this analysis: TIME1 = '2018-06-01' TIME2 = '2017-06-01' PROJECT = itwiki_p, ptwiki_p, plwiki_p, fawiki_p, nlwiki_p

Note: Only people who received a thank are represented in the data.

Note: The "Thanks in Month" and "Thanks in Day" numbers are averages by person only counting the months or days in which a person actually received a thank.

Note: Dif Actual is the difference between the average number of months (or days) on which people actually received thanks and the average number of months (or days) on which they would have received thanks if we spread thanks out randomly. Dif Constant is the difference between the average if we spread thanks out as much as possible and the average if we spread thanks out randomly. Dif Random is the difference between two random spreads.

Conclusion

Thanks appear to be more clustered than they would be if spread out over random days. In other words, people tend to receive thanks in clusters. Further analysis is needed to know exactly what these clusters look like.