Fabian,
I suspect that your primary mistake is in only looking at pages with byte length between 5800 and 6000 bytes. You've severely limited the range of your regressor and therefor invalidated a set of assumptions for the correlation. If you still don't think that you made a mistake, I suggest that you try a scatter plot like the one that I have provided.
As for the regression, it's more informative than a simple pearson correlation because it separates the fitted slope (beta coef) from the fitness of the model (R^2). Without the regression, I could not have plotted the fitted line over the scatter plot.
I've uploaded my code to bitbucket for your reference. Specifically, see:
-Aaron
On Aug 6, 2013 4:17 AM, "Floeck, Fabian (AIFB)" <
fabian.floeck@kit.edu> wrote:
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@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@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@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
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> National Research Center of the Helmholtz Association
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--
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@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
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