This paper (first reference) is the result of a class project I was part of
almost two years ago for CSCI 5417 Information Retrieval Systems. It builds
on a class project I did in CSCI 5832 Natural Language Processing and which
I presented at Wikimania '07. The project was very late as we didn't send
the final paper in until the day before new years. This technical report was
never really announced that I recall so I thought it would be interesting to
look briefly at the results. The goal of this paper was to break articles
down into surface features and latent features and then use those to study
the rating system being used, predict article quality and rank results in a
search engine. We used the [[random forests]] classifier which allowed us to
analyze the contribution of each feature to performance by looking directly
at the weights that were assigned. While the surface analysis was performed
on the whole english wikipedia, the latent analysis was performed on the
simple english wikipedia (it is more expensive to compute). = Surface
features = * Readability measures are the single best predictor of quality
that I have found, as defined by the Wikipedia Editorial Team (WET). The
[[Automated Readability Index]], [[Gunning Fog Index]] and [[Flesch-Kincaid
Grade Level]] were the strongest predictors, followed by length of article
html, number of paragraphs, [[Flesh Reading Ease]], [[Smog Grading]], number
of internal links, [[Laesbarhedsindex Readability Formula]], number of words
and number of references. Weakly predictive were number of to be's, number
of sentences, [[Coleman-Liau Index]], number of templates, PageRank, number
of external links, number of relative links. Not predictive (overall - see
the end of section 2 for the per-rating score breakdown): Number of h2 or
h3's, number of conjunctions, number of images*, average word length, number
of h4's, number of prepositions, number of pronouns, number of interlanguage
links, average syllables per word, number of nominalizations, article age
(based on page id), proportion of questions, average sentence length. :*
Number of images was actually by far the single strongest predictor of any
class, but only for Featured articles. Because it was so good at picking out
featured articles and somewhat good at picking out A and G articles the
classifier was confused in so many cases that the overall contribution of
this feature to classification performance is zero. :* Number of external
links is strongly predictive of Featured articles. :* The B class is highly
distinctive. It has a strong "signature," with high predictive value
assigned to many features. The Featured class is also very distinctive. F, B
and S (Stop/Stub) contain the most information.
:* A is the least distinct class, not being very different from F or G. =
Latent features = The algorithm used for latent analysis, which is an
analysis of the occurence of words in every document with respect to the
link structure of the encyclopedia ("concepts"), is [[Latent Dirichlet
Allocation]]. This part of the analysis was done by CS PhD student Praful
Mangalath. An example of what can be done with the result of this analysis
is that you provide a word (a search query) such as "hippie". You can then
look at the weight of every article for the word hippie. You can pick the
article with the largest weight, and then look at its link network. You can
pick out the articles that this article links to and/or which link to this
article that are also weighted strongly for the word hippie, while also
contributing maximally to this articles "hippieness". We tried this query in
our system (LDA), Google (site:en.wikipedia.org hippie), and the Simple
English Wikipedia's Lucene search engine. The breakdown of articles occuring
in the top ten search results for this word for those engines is: * LDA
only: [[Acid rock]], [[Aldeburgh Festival]], [[Anne Murray]], [[Carl
Radle]], [[Harry Nilsson]], [[Jack Kerouac]], [[Phil Spector]], [[Plastic
Ono Band]], [[Rock and Roll]], [[Salvador Allende]], [[Smothers brothers]],
[[Stanley Kubrick]]. * Google only: [[Glam Rock]], [[South Park]]. * Simple
only: [[African Americans]], [[Charles Manson]], [[Counterculture]], [[Drug
use]], [[Flower Power]], [[Nuclear weapons]], [[Phish]], [[Sexual
liberation]], [[Summer of Love]] * LDA & Google & Simple: [[Hippie]],
[[Human Be-in]], [[Students for a democratic society]], [[Woodstock
festival]] * LDA & Google: [[Psychedelic Pop]] * Google & Simple: [[Lysergic
acid diethylamide]], [[Summer of Love]] ( See the paper for the articles
produced for the keywords philosophy and economics ) = Discussion /
Conclusion = * The results of the latent analysis are totally up to your
perception. But what is interesting is that the LDA features predict the WET
ratings of quality just as well as the surface level features. Both feature
sets (surface and latent) both pull out all almost of the information that
the rating system bears. * The rating system devised by the WET is not
distinctive. You can best tell the difference between, grouped together,
Featured, A and Good articles vs B articles. Featured, A and Good articles
are also quite distinctive (Figure 1). Note that in this study we didn't
look at Start's and Stubs, but in earlier paper we did. :* This is
interesting when compared to this recent entry on the YouTube blog. "Five
Stars Dominate Ratings"
I think a sane, well researched (with actual subjects) rating system
well within the purview of the Usability Initiative. Helping people find and
create good content is what Wikipedia is all about. Having a solid rating
system allows you to reorganized the user interface, the Wikipedia
namespace, and the main namespace around good content and bad content as
needed. If you don't have a solid, information bearing rating system you
don't know what good content really is (really bad content is easy to spot).
:* My Wikimania talk was all about gathering data from people about articles
and using that to train machines to automatically pick out good content. You
ask people questions along dimensions that make sense to people, and give
the machine access to other surface features (such as a statistical measure
of readability, or length) and latent features (such as can be derived from
document word occurence and encyclopedia link structure). I referenced page
262 of Zen and the Art of Motorcycle Maintenance to give an example of the
kind of qualitative features I would ask people. It really depends on what
features end up bearing information, to be tested in "the lab". Each word is
an example dimension of quality: We have "*unity, vividness, authority,
economy, sensitivity, clarity, emphasis, flow, suspense, brilliance,
precision, proportion, depth and so on.*" You then use surface and latent
features to predict these values for all articles. You can also say, when a
person rates this article as high on the x scale, they also mean that it has
has this much of these surface and these latent features.
= References =
- DeHoust, C., Mangalath, P., Mingus., B. (2008). *Improving search in
Wikipedia through quality and concept discovery*. Technical Report.
- Rassbach, L., Mingus., B, Blackford, T. (2007). *Exploring the
feasibility of automatically rating online article quality*. Technical
I have asked and received permission to forward to you all this most
excellent bit of news.
The linguist list, is a most excellent resource for people interested in the
field of linguistics. As I mentioned some time ago they have had a funding
drive and in that funding drive they asked for a certain amount of money in
a given amount of days and they would then have a project on Wikipedia to
learn what needs doing to get better coverage for the field of linguistics.
What you will read in this mail that the total community of linguists are
asked to cooperate. I am really thrilled as it will also get us more
linguists interested in what we do. My hope is that a fraction will be
interested in the languages that they care for and help it become more
relevant. As a member of the "language prevention committee", I love to get
more knowledgeable people involved in our smaller projects. If it means that
we get more requests for more projects we will really feel embarrassed with
all the new projects we will have to approve because of the quality of the
Incubator content and the quality of the linguistic arguments why we should
approve yet another language :)
NB Is this not a really clever way of raising money; give us this much in
this time frame and we will then do this as a bonus...
---------- Forwarded message ----------
From: LINGUIST Network <linguist(a)linguistlist.org>
Date: Jun 18, 2007 6:53 PM
Subject: 18.1831, All: Call for Participation: Wikipedia Volunteers
LINGUIST List: Vol-18-1831. Mon Jun 18 2007. ISSN: 1068 - 4875.
Subject: 18.1831, All: Call for Participation: Wikipedia Volunteers
Moderators: Anthony Aristar, Eastern Michigan U <aristar(a)linguistlist.org>
Helen Aristar-Dry, Eastern Michigan U <hdry(a)linguistlist.org>
Reviews: Laura Welcher, Rosetta Project
The LINGUIST List is funded by Eastern Michigan University,
and donations from subscribers and publishers.
Editor for this issue: Ann Sawyer <sawyer(a)linguistlist.org>
To post to LINGUIST, use our convenient web form at
From: Hannah Morales < hannah(a)linguistlist.org >
Subject: Wikipedia Volunteers
-------------------------Message 1 ----------------------------------
Date: Mon, 18 Jun 2007 12:49:35
From: Hannah Morales < hannah(a)linguistlist.org >
Subject: Wikipedia Volunteers
As you may recall, one of our Fund Drive 2007 campaigns was called the
"Wikipedia Update Vote." We asked our viewers to consider earmarking their
donations to organize an update project on linguistics entries in the
English-language Wikipedia. You can find more background information on this
The speed with which we met our goal, thanks to the interest and generosity
our readers, was a sure sign that the linguistics community was enthusiastic
about the idea. Now that summer is upon us, and some of you may have a bit
leisure time, we are hoping that you will be able to help us get started on
Wikipedia project. The LINGUIST List's role in this project is a purely
organizational one. We will:
*Help, with your input, to identify major gaps in the Wikipedia materials or
pages that need improvement;
*Compile a list of linguistics pages that Wikipedia editors have identified
"in need of attention from an expert on the subject" or " does not cite any
references or sources," etc;
*Send out periodical calls for volunteer contributors on specific topics or
*Provide simple instructions on how to upload your entries into Wikipedia;
*Keep track of our project Wikipedians;
*Keep track of revisions and new entries;
*Work with Wikimedia Foundation to publicize the linguistics community's
We hope you are as enthusiastic about this effort as we are. Just to help us
get started looking at Wikipedia more critically, and to easily identify an
needing improvement, we suggest that you take a look at the List of
Many people are not listed there; others need to have more facts and
added. If you would like to participate in this exciting update effort,
respond by sending an email to LINGUIST Editor Hannah Morales at
hannah(a)linguistlist.org, suggesting what your role might be or which
entries you feel should be updated or added. Some linguists who saw our
on the Internet have already written us with specific suggestions, which we
share with you soon.
This update project will take major time and effort on all our parts. The
result will be a much richer internet resource of information on the breadth
depth of the field of linguistics. Our efforts should also stimulate
students to consider studying linguistics and to educate a wider public on
we do. Please consider participating.
Editor, Wikipedia Update Project
Linguistic Field(s): Not Applicable
LINGUIST List: Vol-18-1831
>>> The people who are loudest in their demands for consensus
>>> do not represent the Wikimedia movement.
>> The voices loudest for the WMF doing something against the
>> Trump administration are not representative of the Wikimedia
>> movement either....
> Is the Community Process Steering Committee currently
> prepared to "engage more 'quiet' members of our community"
> with a statistically robust snap survey to resolve this question?
Anyone can go to Recent Changes and send a SurveyMonkey link to the
most recent few hundred editors with contributions at least a year
old, to get an accurate answer.
Will a respected member of the community please do this? I would like
to know what the actual editing community thinks of the travel ban and
their idea of an appropriate response. I don't want to see community
governance by opt-in participation in obscure RFCs.
I would offer to do this myself, but I value keeping my real name
unassociated with my enwiki userid.
I was asked by a volunteer for help getting stats on the gender gap in
content on a certain Wikipedia, and came up with simple Wikidata Query
Service queries that pulled the total number of articles on a given
Wikipedia about men and about women, to calculate *the proportion of
articles about women out of all articles about humans*.
Then I was curious about how that wiki compared to other wikis, so I ran
the queries on a bunch of languages, and gathered the results into a table,
(please see the *caveat* there.)
I don't have time to fully write-up everything I find interesting in those
results, but I will quickly point out the following:
1. The Nepali statistic is simply astonishing! There must be a story
there. I'm keen on learning more about this, if anyone can shed light.
2. Evidently, ~13%-17% seems like a robust average of the proportion of
articles about women among all biographies.
3. among the top 10 largest wikis, Japanese is the least imbalanced. Good
job, Japanese Wikipedians! I wonder if you have a good sense of what
drives this relatively better balance. (my instinctive guess is pop culture
4. among the top 10 largest wikis, Russian is the most imbalanced.
5. I intend to re-generate these stats every two months or so, to
eventually have some sense of trends and changes.
6. Your efforts, particularly on small-to-medium wikis, can really make a
dent in these numbers! For example, it seems I am personally
responsible for almost 1% of the coverage of women on Hebrew Wikipedia!
7. I encourage you to share these numbers with your communities. Perhaps
you'd like to overtake the wiki just above yours? :)
8. I'm happy to add additional languages to the table, by request. Or you
can do it yourself, too. :)
 Yay #100wikidays :) https://meta.wikimedia.org/wiki/100wikidays
Wikimedia Foundation <http://www.wikimediafoundation.org>
Imagine a world in which every single human being can freely share in the
sum of all knowledge. Help us make it a reality!
In November 2016, I presented the result of a joint research that
helped us understand English Wikipedia readers better. (Presentation
at https://www.youtube.com/watch?v=xIaMuWA84bY ). I talked about how
we used English, Persian, and Spanish Wikipedia readers' inputs to
build a taxonomy of Wikipedia use-cases along several dimensions,
capturing users’ motivations to visit Wikipedia, the depth of
knowledge they are seeking, and their knowledge of the topic of
interest prior to visiting Wikipedia. I also talked about the results
of the study we did to quantify the prevalence of these use-cases via
a large-scale user survey conducted on English Wikipedia. In that
study, we also matched survey responses to the respondents’ digital
traces in Wikipedia’s server logs which enabled us in discovering
behavioral patterns associated with specific use-cases. You can read
the full study at https://arxiv.org/abs/1702.05379 .
==What do we want to do now?==
There are quite a few directions this research can continue on, and
the most immediate one is to understand whether the results that we
observe (in English Wikipeida) is robust across languages/cultures.
For this, we are going to repeat the study, but this time in more
languages. Here are the languages on our list: Arabic, Dutch, English,
Hindi, Japanese, Spanish (thanks to all the volunteers who have been
helping us translating all survey related documents to these
==What about your language?==
If your language is not one of the six languages above and you'd like
to learn about the readers of Wikipedia in it (in the specific ways
described above), please get back to me by Monday, April 24, AoE. I
cannot guarantee that we can run the study in your language, however,
I guarantee that we will give it a good try if you're interested. The
decision to include more languages will depend on: our capacity to do
the analysis, the speed at which your community can help us translate
the material to the language, the traffic to that language, a couple
of sentences on how you'd think the result can help your community,
and your willingness to help us document the results for your language
(Quite some work will need to go to have readable/usable
documentations available and we are too small to be able to guarantee
that on our own for many languages.)
Senior Research Scientist
I am Adele Vrana, Director of Strategic Partnerships at the Foundation.
We have contacts at Amazon and will seek to clarify the questions raised on
this thread. I will make sure to circle back with you once we have an
All the best,
On Thu, Jul 27, 2017 at 10:13 AM, Simon Poole <simon(a)poole.ch> wrote:
> Am 27.07.2017 um 18:37 schrieb Andreas Kolbe:
> > Edward Joseph "Ed" Snowden ...
> > I will not spend an hour trying to identify the exact article version
> > matches Alexa's output in that video best, but it's safe to assume that
> > this inserted "Ed", too, came from Wikipedia, even though it had gone by
> > the time the video was uploaded to YouTube.
> The current (full) answer is
> 'Edward Joseph "Ed" Snowden, the American computer professional former
> CIA employee, and government contractor who leaked classified
> information from the U.S. National Security Agency in 2013.'
> Now obviously there could be -lots- going on behind the scenes, for
> example long term caching of search results (difficult to believe that
> Bing would allow that if it is really from them, but who knows) and so on.
> Wikimedia-l mailing list, guidelines at: https://meta.wikimedia.org/
> wiki/Mailing_lists/Guidelines and https://meta.wikimedia.org/
> New messages to: Wikimedia-l(a)lists.wikimedia.org
> Unsubscribe: https://lists.wikimedia.org/mailman/listinfo/wikimedia-l,
*Strategic Partnerships - Global Reach*
+1 (415) 839-6885 ext. 6773
*Imagine a world in which every single human being can freely share in the
sum of all knowledge. That's our commitment. Donate.
Hi list members,
The list admins (hereafter 'we', being Austin, Asaf, Shani and I, your
humble narrator) regularly receive complaints about the frequent
posters on this list, as well as about the unpleasant atmosphere some
posters (some of them frequent) create.
It is natural that frequent posters will say specific things that more
frequently annoy other list members, but often the complaints are due
to the volume of messages rather than the content of the messages.
We are floating some suggestions aimed specifically at reducing the
volume, hopefully motivating frequent posters to self-moderate more,
but these proposed limits are actually intending to increasing the
quality of the discourse without heavy subjective moderation.
The first proposal impacts all posters to this list, and the last
three proposals are aimed at providing a more clear framework within
which criticism and whistle-blowing are permitted, but that critics
are prevented from drowning out other discussions. The bandwidth that
will be given to critics should be established in advance, reducing
need to use subjective moderation of the content when a limit to the
volume will often achieve the same result.
Proposal #1: Monthly 'soft quota' reduced from 30 to 15
The existing soft quota of 30 posts per person has practically never
been exceeded in the past year, and yet many list subscribers still
clearly feel that a few individuals overwhelm the list. This suggests
the current quota is too high.
A review of the stats at
https://stats.wikimedia.org/mail-lists/wikimedia-l.html show very few
people go over 15 in a month, and quite often the reason for people
exceeding 15 per month is because they are replying to other list
members who have already exceeded 15 per month, and sometimes they are
repeatedly directly or indirectly asking the person to stop repeating
themselves to allow some space for other list members also have their
Proposal #2: Posts by globally banned people not permitted
As WMF-banned people are already banned from mailing lists, this
proposal is to apply the same ‘global’ approach to any people who have
been globally banned by the community according to the
This proposal does not prevent proxying, or canvassing, or “meat
puppetry” as defined by English Wikipedia policy. The list admins
would prefer that globally banned people communicate their grievances
via established members of our community who can guide them, rather
than the list admins initially guiding these globally banned people on
how to revise their posts so they are suitable for this audience, and
then required to block them when they do not follow advice. The role
of list moderators is clearer and simpler if we are only patrolling
the boundaries and not repeatedly personally engaged with helping
globally banned users.
Proposal #3: Identity of an account locked / blocked / banned by two
Wikimedia communities limited to five (5) posts per month
This proposal is intended to strike a balance between openness and
quality of discourse.
Banned people occasionally use the wikimedia-l mailing list as a
substitute of the meta Request for comment system, and banned people
also occasionally provide constructive criticisms and thought
provoking views. This proposal hopes to allow that to continue.
However people who have been banned on a few projects also use this
list as their “last stand”, having already exhausted the community
patience on the wikis. Sometimes the last stand is brief, but
occasionally a banned person is able to maintain sufficient decorum
that they are not moderated or banned from the list, and mailing list
readers need to suffer month after month of the banned person
dominating the mailing lists with time that they would previously have
spent editing on the wikis.
Proposal #4: Undisclosed alternative identities limited to five (5)
posts per month
Posting using fake identities allows people to shield their real life
*and* their Wikimedia editing 'account' from the repercussions of
their actions. This provision to allow fake identities on wikimedia-l
is necessary for whistle-blowing, and this mailing list has been used
for that purpose at important junctures in the history of the
However it is more frequently abused, especially by some ‘critics’ who
have used incessant hyperbole and snark and baiting to generally cause
stress to many readers. Sometimes this is also accompanied with many
list posts on various unrelated threads as the ‘critic’ believes their
criticism is so important that all other discussions about Wikimedia
should be diverted until their problem has been resolved to their
satisfaction, which is unlikely anyway.
Note this explicitly does not include anyone posting using their real
world identity, whether or not they have a Wikimedia account.
Where a poster does not clearly link to either Wikimedia account, or
does not appear to be using a real identity, and only after it is
exceeding the five post limit, the list admins will privately ask the
poster to either verify their identity or stop posting until the end
of the month. Very frequently a whistle-blower is able and even
prefers to be documenting the problem on meta, but needs the high
profile of this list to spark the discussion and draw attention to
their meta page.
The five post allowance for proposals 3 and 4 are to ensure that
anyone who has not been globally banned can post criticisms without
repercussions, which is vital for whistleblowing and transparency
generally, but they need to use their five posts per month wisely.
Once they have used their five posts, community members can reply with
less concern about being drawn into a direct argument with the poster.
It aims to force the poster to listen to others in the community once
their limit of five posts has been reached.
If there is support for these proposals, the list admins would not
immediately add moderation or bans, but would implement them as
needed, when we notice someone has exceeded one of these limits, and
we would make a note on a meta page where the community can review
these actions without allowing moderation meta-discussion to dominate
the discourse on the mailing list. Refinements to the list moderation
limits can then occur organically as we see how these rules plays out
The RFC is at https://meta.wikimedia.org/wiki/Requests_for_comment/wikimedia-l-post-limits
However please also feel welcome to reply on-list if you wish to
express explicit support or opposition to any of the four proposals
above (please identify them by number, to ease counting). We will
count votes (here and on the meta RFC) after two weeks, and post a
more refined final version back to this mailing list.
The list administrators will default to *enacting* all four proposals,
but will refrain from enacting any proposal receiving more opposition
Those of you running Windows 10 will be familiar with the
regularly-changing "lockscreen" images showing things like beautiful
scenery and scenes from nature:
The last one I just saw was labelled "copyright [photographer name]
Is there someone at WMF, with contacts at Microsoft, who could
persuade them to use some featured images from Commons, with a small
piece of text explaining that people may upload their own images?
That would seem to be a simple way to do a massive piece of outreach,
to a new audience.