Impact is a combined measure of recommendations and comments that I use in daily and weekly lists summarizing recently published diaries.
For the details on impact, see the extended diary. For recent daily and weekly diary lists constructed based on impact, see my diaries.
I'll also take this opportunity to point out a half year round up diary that may interest more people than it reached the first time around (based on some recent questions).
This diary replaces a previous diary on the same subject which is now frequently archived and so unavailable.
Recommendations and comments accrue seemingly independently of each other. Some diaries get lots of recommendations but few comments, and vice versa.
A list based on either recommendations or comments alone will leave out some diaries that a lot of people have paid attention to.
For that reason, I wanted to use a measure that combines both. The only way I could think of to do this was by comparison to a standard, but that is of course the way if most "weights and measures".
The standard unit of diary impact I chose to use, and I hope others will approve of, is Bill In Portland Maines long running series, Cheers and Jeers. The unit associated is, naturally, the C&J, or as I prefer to call it, the bharns. One bharns is supposed to be the equivalent of the impact of one Industry Standard C&J diary. I believe this may be the first unit of measure named after an email address.
I derived the unit by collecting the average number of recommendations and comments received by each BiPM authored C&J recieved during the first quarter of 2005.
For those who've made it this far, here is the python code I use to calculate impact.
def impact(nrec,ncom):
# calculate impact relative to a standard diary
# namely BiPM's Cheers and Jeers
# Between Jan 1, 2005 and April 4 2005 there were
# 53 new week day issues of C&J. The average number of
# recommendations received was 79.71, stdev = 11.38
# and the average number of comments added to each was
# 412.69, stdev = 72.71.
# Defining these levels equivalent to 1 bharns of impact
# it is possible to calculate the relative impact of any diary
# from the number of recommendations (nrec) and the
# number of comments, ncom.
rimpact = nrec / 79.71
cimpact = ncom / 412.69
impact = ((rimpact * rimpact) + (cimpact * cimpact)) / 2.0
impact = math.sqrt(impact)
return impact
Please note that impact is not, and is not intended to be, a measure of diary quality, and that publication of lists based on diary impact is solely for the purpose of making available well received diaries to those who, like me, can't spend 24x7 here at Daily Kos.