Here's a plot that should have been included in
part three of Mining Jobmine. It describes the change in distribution of applications as the length of job posting changes. For each x-value representing a certain length of job posting, the plot gives an estimate on the portion of jobs that has 0 to 22 applications, 23 to 40 applications, 41 to 70 applications and >71 applications. The end points are chosen to be the 25th, 50th and 75th percentiles of the number of applications.

The size of the "0 to 22 applications" category increases steadily as the length of job posting increases from 30-ish to around 500, indicating a drop in application. But as the length of job posting increases beyond 500 words, the size of the bottom-most category decreases. This decrease is offset by an increase in the size of the ">71" category. My guess is that jobs with really long job postings are
ones where multiple positions are advertised (e.g. Google job posting...).
Compared to what I had before, this is a much better way of visualizing the correlation between length of job posting and application.
End of Entry
Hmmm... maybe the really long job descriptions have a lot of technical descriptions... XD
ReplyDeletehey dude, i like what you're doing... a lot
ReplyDeletewhat do you use for generating those graphs ?
thanks
these are base R graphics, produced using R. (the ggplot2 package in R makes even better graphics http://had.co.nz/ggplot2/ )
ReplyDeleteThanks Lisa, this kind of thing pretty much makes me drool... Making it to the Facebook data team or something similar is pretty much a dream for me. Any tips?
ReplyDeletethanks