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
After reading an interesting related discussion on GenderGap, I have
queried the top 10 users of the thanks feature last month, on both the
English Wikipedia and Commons. Snapshot image attached and report link
Perhaps someone might think of a suitable barnstar and award these
folks for "being nice"? :-)
P.S. This is a long query to run, taking 20 to 30 minutes due to the
nature of the logging tables. However if someone wanted to make a
monthly summary on-wiki somewhere, part of an active "be nice"
campaign, I would be happy to set up an automated monthly report (if
someone discovers this is already reported somewhere, that's cool we
can use that).
It is an honor to announce that the Affiliations Committee has resolved
 recognizing the Wikimedia User Group China as a Wikimedia User
Group; their main focus areas are getting more chinese people know and
use Wikipedia, encouraging people to become contributors to the
different Wikimedia projects, and maintain the community healthy and
growing. Let's welcome the newest member of the family of affiliates
-and the fourth from the Sinosphere!
"*Jülüjain wane mmakat* ein kapülain tü alijunakalirua jee wayuukanairua
junain ekerolaa alümüin supüshuwayale etijaanaka. Ayatashi waya junain."
Carlos M. Colina
Vicepresidente, A.C. Wikimedia Venezuela | RIF J-40129321-2 |
Chair, Wikimedia Foundation Affiliations Committee
This is a personal note to clarify a some questions that recently came up,
specifically in the context of my role as the incoming ED.
My partner Wil and I are partners in our private lives. We have always both
been extremely independent, and we respect that in each other. That said we
have different roles: I am the Executive Director with responsibilities
towards the Foundation and the movement, and he is an independent community
member with his own voice.
I make my decisions using my own professional judgement in conjunction with
input from the community and staff. I don’t consult Wil on these matters,
ask him to do anything on my behalf or monitor his engagements with the
community. When I speak here, it is in my capacity as an ED.
Wil, on the other hand, has a very strong personal interest in the
community and agreat deal of curiosity about how the Wikimedia
projectswork. It is very important to him that he remains an
able to speak with his own voice and ask his own questions. He does not
take direction from me. He will not work for the WMF or engage with the WMF
I hope this addresses some of the questions and draws distinction between
my role as ED and Wil’s participation as an independent member. If you have
any questions for Wil you can reach him directly. If you have any questions
for me or the WMF, you can get a hold of me by email or on my talk page.
I am Wikipedian in residence and want to upload a high quality tiff archive
and I can't seem to upload more than 100.00 MB. I get this message: "You
can only upload files with a size of up to 100.00 MB". What is happening ?
Do you know what I can do?
*"Wikipedia es algo especial. Es como una biblioteca o un parque público.
Es como un templo para el pensamiento. Un lugar al que todos podemos ir a
pensar, a aprender, a compartir nuestros conocimientos con otros." JW*
Carmen Alcázar (@metik)
Secretaria, Wikimedia <https://www.facebook.com/wikimediamx>México A.C.
Coordinadora Hospitalidad Wikimanía
I'm asking this on Wikimedia-l because a number of Wikimedians have noted
the expensiveness of the San Francisco area including its high cost of
living for staff, employer competition for engineering talent, and
associated high salaries for WMF employees.
I see on
that WMF is considering relocating its offices when its current main office
What happens to the remodel expenses that WMF is paying for at its current
location? If WMF vacates the premesis, will it be compensated for the
remodel by the building owner?
I hope that WMF is contemplating fully exiting the San Francisco market
area in order to economize, get better value for our donors' funds, have
less competition for talent, and lower costs of living for staff. Is this
Thanks very much,
We are the Finance Fellows, a multicultural team consisting of 4 young
professionals. We are happy to introduce a 6-month movement-wide project
that focuses on the consistency of how we operate, which is explained
further in this announcement.
*But here's some information about us*:
Arda [User:Melmas_(WMF)] <https://meta.wikimedia.org/wiki/User:Melmas_(WMF)> is
from Turkey. He holds a BA in Economics.
<https://meta.wikimedia.org/wiki/User:Lgillis_(WMF)> is from Belgium. She
holds a Master's degree in Applied Economics and a Master's degree in
<https://meta.wikimedia.org/wiki/User:Oolukoya_(WMF)> is from Nigeria. She
holds a Master's in International Business and a BSc in Economics.
<https://meta.wikimedia.org/wiki/User:Wagsegura_(WMF)> is from Nicaragua.
He holds a BA in Applied Economics.
*About the project "Movement-wide financial report"*
Driven by the Wikimedia Foundation's guiding principles of transparency and
accountability, our goal is to gather data and develop systematic metrics
in order to provide a better understanding of financial statements. The aim
is to help make financial data and statements more consistent and
comparable across all Wikimedia Chapters, Thematic Organizations, and the
Wikimedia Foundation, to the benefit of the whole movement.
The idea of this project comes from the WMF Board of Trustee's Audit
Committee and is supported by the Wikimedia Foundation. An initial quantitative
analysis of Wikimedia Chapters and Thematic Organizations
at Wikimania 2013 by Michal Buczyński (User:Aegis Maelstrom)
<https://en.wikipedia.org/wiki/User:Aegis_Maelstrom>, highlighted the
importance of meaningful, obtainable and unified data.
The Finance Fellows have been formed by WMF to spearhead this project. The
intention of this project is to enable Wikimedia Chapters and Thematic
Organizations to benchmark activities and costs in a consistent way. We
will begin by gathering comparable quantitative financial data about
Wikimedia Chapters and Thematic Organizations. Our findings will later be
released movement-wide, on Meta-Wiki.
Please note that this is not an audit process. We are simply collecting the
data and developing global metrics. The metric is an objective measurement
that will enable data to be consistent, meaningful and comparable among the
Wikimedia Chapters, Thematic Organizations, and the Wikimedia Foundation.
We will build on existing data sets and reach out to Chapters and Thematic
Organizations if further information is required. After processing the
gathered information, we will confirm the data with each organization.
In the long run, we envision that this project could be replicated
annually. In this attempt to enable Wikimedia Chapters, Thematic
Organizations, and the Wikimedia Foundation to help make the movement's
financial data more consistent, we rely on the data provided by the
organizations. We believe that there is enough data available to make a new
attempt on capturing the movement's finances as a whole.
A meta page <https://meta.wikimedia.org/wiki/Movement-wide_Financial_Report>
created for the project, in order to make the information accessible to
everyone and create a space for discussion and/or suggestions. We strongly
encourage you to share with us what types of additional information is
And of course: This is all an experiment! If it does not work, we will try
to apply a modified 'agile' process by iterating, repeating, and trying
again based on the feedback we are getting. If this does not seem right, or
if it appears we are missing something obvious, please let us know!
WMF Finance Fellows (User:WMF Finance Fellows)
[ cross-posted to MediaWiki-i18n, Wikimedia-L and Wikitech-L ]
The 2000th article that was written using the ContentTranslation extension
was published today.
Article #2000 was translated from English to Greek, and it's about Škocjan
Caves, a UNESCO World Heritage site in Slovenia.
In case you're wondering what ContentTranslation is, here's a brief
summary: ContentTranslation is an extension that helps Wikipedia editors to
create articles quickly and easily by translating them from other
languages. It's being developed by the Language Engineering team. Its
design started in the summer of 2013 and its coding started in early 2014.
You can find more info at https://www.mediawiki.org/wiki/CX as well as in
the following blog posts:
Some more data about ContentTranslation:
* Our first deployment was in mid-January to Catalan, Spanish, Portuguese,
Esperanto, Norwegian Bokmal, Danish, Indonesian and Malay. Now we support
43 languages, and this number is growing every week as we extend the
deployment (a special thank-you to the Ops and Release Engineering people,
who continuously and tirelessly support our deployment effort).
* In all the Wikipedias in which ContentTranslation is deployed, it is
currently defined as a Beta feature, which means that it is only available
to logged-in users who opted into it in the preferences.
* The 1000th article was written on April 10th, so it took much less to get
to 2000 than to 1000.
* The language into which the most articles were translated is Catalan:
762. The Catalan Wikipedia community always had a strong inclination to
translation, it was the first one that volunteered to test the tool in labs
in the summer of 2014 and provided a lot of useful feedback, and it also
has good machine translation support thanks to the Freely-licensed Apertium
* The second most popular target language is Spanish. It started slowly in
the first couple of months, but it's quickly growing since March.
* Other target languages that are quickly growing lately are French,
Portuguese and Ukrainian.
* The language from which the largest number of articles is translated is
English. It is followed by Spanish, from which a lot of articles are
translated to the closely related Portuguese and Catalan.
* The total number of people who published at least one translated article
into any language is 663.
* Of more than 2000 articles that were created, about 60 were deleted, so
we have a reason to think that the quality of the created articles is
* In Catalan we see that ContentTranslation has some influence on the
number of articles created per day - it was usually between 60 and 90
before 2015, and in January and February it was over a 100. It's too early
to say how does it influence other languages, but we are optimistic ;)
* A community discussion about enabling the tool in the French Wikipedia
ended with 50 "votes" in support of the tool and 0 "votes" against it ;)
Some of our plans for the coming months are:
* Enabling more languages, including big ones like English, Russian and
Italian, as well as right-to-left languages.
* Improving the support for links.
* Creating support for smart suggestions of articles to translate, as well
as "task lists" for translation projects.
* Starting to get the tool out of beta status :)
I'd like to thank all the Wikimedia volunteers around the planet who are
participating in this effort by translating articles, translating the
extension's user interface, testing the tool, assisting other wikipedians
to translate, organizing translation workshops, reporting useful bugs,
submitting patches, and generally proving day after day what an incredible
community they are - hard-working, massively-multilingual, helpful,
patient, creative and talented.
Thank you - we have a lot more to achieve together \o/
Amir Elisha Aharoni · אָמִיר אֱלִישָׁע אַהֲרוֹנִי
“We're living in pieces,
I want to live in peace.” – T. Moore