On Fri, Jun 4, 2010 at 8:16 AM, Brian <[email protected]> wrote:
> > > On Thu, Jun 3, 2010 at 4:14 PM, Reid Priedhorsky <[email protected]> wrote: > >> Brian J Mingus wrote: >> > ---------- Forwarded message ---------- >> > From: Brian <[email protected]> >> > Date: Wed, Jun 2, 2010 at 10:46 PM >> > Subject: Re: [Wiki-research-l] Quality and pageviews >> > To: Liam Wyatt <[email protected]> >> > >> > >> > 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/DeHoustMangalathMingus08_feature_table.png > > 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. > > Single best predictor overall: Automated Readability Index http://en.wikipedia.org/wiki/Automated_Readability_Index
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