I'm into
AnalyzingWiki. I just don't look a lot at the contents, but at the activities.
It seems the huge majority of the people who make an edit just make one edit.
Finally, I've got all into a block_graphics.
When I make both the x_axis and the y_axis use a logarithmic scale, I just see a straight line, going down, with a small hump at the end - something like this:
|\
| \
| \ y-axis = log(number of people)
| \ x-axis = log(number of pages)
| \
| \/\
(see also end of page, if luck is on)
So the graphics show how many people edited how many pages.
I think this graphics show a general rule. For instance in all kind of sports.
Most people aren't involved at all.
A lot of people are involved a little.
Some people are involved a lot.
Only very few people are involved a real lot
I figure when you study how many people are involved in a sport, and you measure the time they spent in this sport and put these two values in a loglog graphic, it will generate a straight line.
This is contrary to a normal distribution, well maybe someone can explain this some day later.
Why would you expect a normal distribution in the first place?
About the lump: The most active people also do a lot of small edits. The people in this lump are the real community. The lump causes the self-repairing activity.
Q How do you know that "the lump causes the self-repairing activity"? How do you know that "the people in this lump are the real community"?
A Well I do not "know" this, I think this, so this is my interpretation. If I look at the contents of the data it also seems this way. The data is all Changes
In<Months> and
RecentEdits, so you can check it out yourself too.
Another interpretation: Still, this huge mass of people who just pass by and aren't involved are needed, to generate a small community. So this huge mass of people is the backbone. If you look around to other
WikiWikis you will find a lot with just occasional edits, and those
WikiWikis are mere guestbooks. Those
WikiWikis are not really alive.
"LogLog"
h
ttp://www.leescafe.freeservers.com/gif/loglog.gif
Note: remote embedding of this image is disallowed by freeservers.com. Copy and paste the URL into your browser.
A straight line on a log-log plot means log
y =
A log
x +
B, which means
y =
C x^
k. In this case, it looke as if
k is close to -1, which would suggest an instance of
ZipfsLaw.(
http://mathworld.wolfram.com/ZipfsLaw.html )
Well, the line hits the X_axis at
about log(400) and it hits the Y_axis at
about log(2000).
( about = a citation from my memory
).
See also:
WhyLogLog
See
WikiWordStatistics for another example of a
PowerLaw distribution.