Hoi, I am a big fan of suggesting people to write articles / do work that will be read, will be used. In a blogpost [1], I suggest the accumulation of these click streams and use the missing popular articles as suggestions for new articles. Articles that people seek and are truly missing are also obvious candidates as suggestions for new articles.
My question: how hard is it to do this accumulation and analysis for missing new articles and, combine it with suggestions to authors to write something that is likely to prove popular? Does this idea have merit? Thanks, GerardM
[1] https://ultimategerardm.blogspot.nl/2018/01/wikipedia-entering-rabbit-hole.h...
On 18 January 2018 at 21:37, Joseph Allemandou jallemandou@wikimedia.org wrote:
Hi Gerard, Here are my two cents on your questions.
About redlinks, you are correct in saying that the 3% of "other" link-type are jumps from a page to another (using http-referer), while the hyperlink from the origin to the target allowing for such a jump doesn't exist in the origin page at the moment of computation. From my exploration of the dataset, such "other" links happen with the "manually-edited-with-error" url class (the "-" article has a lot of such entering links for instance), as well as with links that I think have been edited in the origin page (for instance in November 2017 dataset, there are "other" links from page "Kevin Spacey" to "Dan Savage", "hebephilia","pedophilia or "Harvey_Weinstein" - Those links are confirmed as existing at some point in the page in November, but not anymore at the beginning of December when the pages hyperlinks are snapshot).
As for your question about what people are looking for and don't find, the one way I can think of to get ideas is to use detailed session analysis correlated with search results, in order to try to get a signal of pages reached from search and not being visited for long. Even if I think we have data we could use in that respect on the cluster, we can't publish such details externally for privacy concerns, obviously.
Please let me know if what I say makes sense :) Many thanks Joseph Allemandou
Hoi, Do I understand well that the 3% of "other" links are the ones that have articles at *this *time but they did not exist at the time of the dump. So
in effect they are not red links?
Is there any way to find the articles people were seeking but could not find?? Thanks, GerardM
On 16 January 2018 at 20:21, Leila Zia leila@wikimedia.org wrote:
Hi all,
For archive happiness:
Clickstream dataset is now being generated on a monthly basis for 5 Wikipedia languages (English, Russian, German, Spanish, and Japanese).
You
can access the data at https://dumps.wikimedia.org/other/clickstream/
and
read more about the release and those who contributed to it at https://blog.wikimedia.org/2018/01/16/wikipedia-rabbit-hole-
clickstream/
Best, Leila
-- Leila Zia Senior Research Scientist Wikimedia Foundation
On Tue, Feb 17, 2015 at 11:00 AM, Dario Taraborelli < dtaraborelli@wikimedia.org> wrote:
We’re glad to announce the release of an aggregate clickstream dataset extracted from English Wikipedia
http://dx.doi.org/10.6084/m9.figshare.1305770
This dataset contains counts of *(referer, article) *pairs aggregated from the HTTP request logs of English Wikipedia. This snapshot
captures
22
million *(referer, article)* pairs from a total of 4 billion requests collected during the month of January 2015.
This data can be used for various purposes: • determining the most frequent links people click on for a given
article
• determining the most common links people followed to an article • determining how much of the total traffic to an article clicked on a link in that article • generating a Markov chain over English Wikipedia
We created a page on Meta for feedback and discussion about this
release:
https://meta.wikimedia.org/wiki/Research_talk:Wikipedia_clickstream
Ellery and Dario
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*Dario Taraborelli *Director, Head of Research, Wikimedia Foundation wikimediafoundation.org • nitens.org • @readermeter http://twitter.com/readermeter
-- *Joseph Allemandou* Data Engineer @ Wikimedia Foundation IRC: joal
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