On Fri, Jun 4, 2010 at 8:16 AM, Brian <Brian.Mingus(a)colorado.edu> wrote:
On Thu, Jun 3, 2010 at 4:14 PM, Reid Priedhorsky <reid(a)umn.edu> wrote:
Brian J Mingus wrote:
---------- Forwarded message ----------
From: Brian <Brian.Mingus(a)colorado.edu>
Date: Wed, Jun 2, 2010 at 10:46 PM
Subject: Re: [Wiki-research-l] Quality and pageviews
To: Liam Wyatt <liamwyatt(a)gmail.com>
Interestingly, the result is negative. The correlation coefficient
between
2500 featured articles and 2500 random articles
is .18 which is very
low. I
also trained a linear classifier to predict the
quality of an article
based
on the number of page views and it was no better
than chance.
That reminds me of an incidental finding from our 2007 work: we wanted
to use article edit rate to predict view rate, but there was no
correlation between the two.
Reid
That is an interesting negative finding as well. Just so this thread
doesn't go without some positive results, here is a table from one of my
technical reports on some features that *do* correlate with quality. If
the number is greater than zero it correlates with quality, if it is 0 it
does not correlate, and if it is less than 0 it is negatively correlated
with quality. The scale of the numbers is meaningless and not interpretable,
although the relative magnitude is important. These are just the relative
performance of each feature for each class, as extracted from the weights of
a random forests classifier.
http://grey.colorado.edu/mediawiki/sites/mingus/images/1/1e/DeHoustMangalat…
Summary (features in order of predictive ability):
- *Featured* articles are *correlated* with Number of images, Number of
external links, Automated Readability Index, Number of references, Number of
internal links, Length of article HTML, Gunning Fog Index, Flesch-Kincaid
Grade Level, Lesbarhedsindex Readability Formula, Number of words, Number of
to be's, Number of sentences
- Note that featured articles are easy to predict.
- *A* articles are *correlated* with Number of references, PageRank,
Number of external links, Number of images, Article age (page-id).
- Note that A articles are extremely hard to predict. All of the
above A predictors are weaker than all of the featured predictors. This
class should be merged with another quality class.
- *G *articles are *correlated* with Number of external links, Number
of templates, Number of references, Automated Readability Index,
Flesh-Kincaid Grade Level
- *G* articles are *negatively correlated* with Length of article HTML,
Flesch Reading Ease, Smog Grading
- Note that G articles are extremely hard to predict and should be
merged with another quality class.
- *B* articles are *correlated* with Automated Readability Index,
Flesch-Kincaid Grade Level, Laesbarhedsindex Readability Formula, Gunning
Fog Index, Length of Article HTML, Number of paragraphs, Flesh Reading Ease,
Smog Grading, Number of internal links, Number of words, Number of
references, Number of to be's, Number of sentences, Coleman-Liau Index,
Number of templates, PageRank, Number of external links, Number of relative
links, Number of <h3>s, Number of interlanguage links
- Note that B articles are very easy to predict.
- *Start/Stub* were left out of this analysis because they are so easy
to predict based on a lack of pretty much any useful information.