still consider myself a noobie in ds here, so I may be asking a very easy and stupid question, but would really appreciate some guidance.
The hypothetical situation is that, you have a website where users write let's say movie reviews. So there are in general two types of users on your website, the ones who write normal amount like the rest of us, and the ones who write very often and are so called "top contributors".
Now the question is, how would you, using data, to define who are "top contributors"?
My idea was that, we'll take the last 24 weeks (~6 months) data, then we take the average daily contributions per user over each week, then we take average of these averages for each user. Then, with the average rate calculated, we can list out the top contributors overall or for each region. So basically:
for each user:
daily_avg = [# of contributions]/[# of days] where [# of days]=7
weekly_avg = [sum of daily_avg]/[# of weeks] where [# of weeks]=24
My questions are:
- Does my approach make sense?
- Would love to learn from your better approaches.
-- notes --
The reason why I picked only the past 6 months instead of all time, is because in case some users used to be extremely active but no longer is.
Again, here to learn from everyone. Appreciate any critique or suggestions! Thanks.
