Hi,
thanks for your feedback Jonathan and Aaron.
@Jonathan: You are rightfully pointing at some things that could have been done
differently, as this was just an ad-hoc experiment. What I did was getting the curl
result of
"http://en.wikipedia.org/w/api.php?action=parse&prop=text&pageid=X" and
running it through BeautifulSoup [1] in Python.
Regarding references: yes, all the markup was stripped away which you cannot see in form
of readable characters as a human when you look at an article. Take as an example [2]: in
the final output (which was the base for counting chars) what is left in characters of
this reference is the readable "[1]" and " ^ William Goldenberg at the
Internet Movie Database".
Regarding alt text: it was completely stripped out. This can arguably be done different,
if you see it as "readable main article text" as well.
You are sure right that including these would lead to a higher correlation. Looking at
samples from the output, the increase in correlation will however not be very big, but
that's a mere hunch. Anyway, this was not what I was looking for. I wanted to compare
really only the readable text you see directly when scrolling through the article.
What is another issue is the inclusion of expandable template listings as I mentioned in
my first mail. Are the long listings of related articles "main, readable article
text"? I suppose not, but we did not filter them out yet.
@Aaron, I'm pretty sure I didn't make a mistake, but before I can answer your
mail: What exactly does this content_length API call give you back (I'm not aware of
that). Takes the Wikisyntax and strips it of tags and comments? Or the HTML shown in the
front-end including all content generated by templates minus all mark-up? Only in the
ladder case would this be comparable in any way to what I have done. Please clarify and
send me the concrete API call. I don't think your content_length is the length of the
readable front-end text as I used it.
(On a side note: I'm unsure why you paste the complete results of a linear regression,
as a Pearson correlation will perfectly suffice in such a simple bivariate case. They -
due to the nature of these statistical methods - of course yield the same results in this
case. Or was there any important extra information that I missed in these regression
results?).
Best,
Fabian
[1]
http://www.crummy.com/software/BeautifulSoup/bs4/doc/
[2]
http://en.wikipedia.org/wiki/William_Goldenberg#cite_note-1
On 05.08.2013, at 01:15, Aaron Halfaker <aaron.halfaker(a)gmail.com> wrote:
(note that I posted this yesterday, but the message
bounced due to the attached scatter plot. I just uploaded the plot to commons and
re-sent)
I just replicated this analysis. I think you might have made some mistakes.
I took a random sample of non-redirect articles from English Wikipedia and compared the
byte_length (from database) to the content_length (from API, tags and comments
stripped).c
I get a pearson correlation coef of 0,9514766.
See the scatter plot including a linear regression line. See also the regress output
below.
Call:
lm(formula = byte_len ~ content_length, data = pages)
Residuals:
Min 1Q Median 3Q Max
-38263 -419 82 592 37605
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -97.40412 72.46523 -1.344 0.179
content_length 1.14991 0.00832 138.210 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 2722 on 1998 degrees of freedom
Multiple R-squared: 0.9053, Adjusted R-squared: 0.9053
F-statistic: 1.91e+04 on 1 and 1998 DF, p-value: < 2.2e-16
On Mon, Aug 5, 2013 at 12:59 AM, WereSpielChequers <werespielchequers(a)gmail.com>
wrote:
Hi Fabian,
That's interesting. When you say you stripped out the html did you also strip out the
other parts of the references? Some citation styles will take up more bytes than others,
and citation style is supposed to be consistent at the article level.
It would also make a difference whether you included or excluded alt text from readable
material as I suspect it is non granular - ie if someone is going to create alt text for
one picture in an article they will do so for all pictures.
More significantly there is a big difference in standards of referencing , broadly the
higher the assessed quality and or the more contentious the article the more references
there will be.
I would expect that if you factored that in there would be some correlation between
readable length and bytes within assessed classes of quality, and the outliers would
include some of the controversial articles like Jerusalem (353 references)
Hope that helps.
Jonathan
On 2 August 2013 18:24, Floeck, Fabian (AIFB) <fabian.floeck(a)kit.edu> wrote:
Hi,
to whoever is interested in this (and I hope I didn't just repeat someone else's
experiments on this):
I wanted to know if a "long" or "short" article in terms of how much
readable material (excluding pictures) is presented to the reader in the front-end is
correlated to the byte size of the Wikisyntax which can be obtained from the DB or API; as
people often define the "length" of an article by its length in bytes.
TL;DR: Turns out size in bytes is a really, really bad indicator for the actual, readable
content of a Wikipedia article, even worse than I thought.
We "curl"ed the front-end HTML of all articles of the English Wikipedia (ns=0,
no disambiguation, no redirects) between 5800 and 6000 bytes (as around 5900 bytes is the
total en.wiki average for these articles). = 41981 articles.
Results for size in characters (w/ whitespaces) after cleaning the HTML out:
Min= 95 Max= 49441 Mean=4794.41 Std. Deviation=1712.748
Especially the gap between Min and Max was interesting. But templates make it possible.
(See e.g. "Veer Teja Vidhya Mandir School", "Martin Callanan" --
Allthough for the ladder you could argue that expandable template listings are not really
main "reading" content..)
Effectively, correlation for readable character size with byte size = 0.04 (i.e. none) in
the sample.
If someone already did this or a similar analysis, I'd appreciate pointers.
Best,
Fabian
--
Karlsruhe Institute of Technology (KIT)
Institute of Applied Informatics and Formal Description Methods
Dipl.-Medwiss. Fabian Flöck
Research Associate
Building 11.40, Room 222
KIT-Campus South
D-76128 Karlsruhe
Phone: +49 721 608 4 6584
Fax: +49 721 608 4 6580
Skype: f.floeck_work
E-Mail: fabian.floeck(a)kit.edu
WWW:
http://www.aifb.kit.edu/web/Fabian_Flöck
KIT – University of the State of Baden-Wuerttemberg and
National Research Center of the Helmholtz Association
_______________________________________________
Wiki-research-l mailing list
Wiki-research-l(a)lists.wikimedia.org
https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
_______________________________________________
Wiki-research-l mailing list
Wiki-research-l(a)lists.wikimedia.org
https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
<ATT00001.c>
--
Karlsruhe Institute of Technology (KIT)
Institute of Applied Informatics and Formal Description Methods
Dipl.-Medwiss. Fabian Flöck
Research Associate
Building 11.40, Room 222
KIT-Campus South
D-76128 Karlsruhe
Phone: +49 721 608 4 6584
Fax: +49 721 608 4 6580
Skype: f.floeck_work
E-Mail: fabian.floeck(a)kit.edu
WWW:
http://www.aifb.kit.edu/web/Fabian_Flöck
KIT – University of the State of Baden-Wuerttemberg and
National Research Center of the Helmholtz Association