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
now we are approaching 400 days of lila tretikov at the helm of the
wikimedia foundation, and 60 million us dollars spent, i was not able
to sign a simple wikipedia page via the mobile app. i think something
is going seriously wrong here :(
what was the use case? the european union wants to harmonize the
freedom of panorama:
german wikipedia had a wikipedia banner to sign a petition, and also
wrote mails about it. which i thought is a nice idea. i am reading
mails on the phone following links to wikipedia, i tried it this time
as well, and i was not able to accomplish the most simple task of
contribution - to add my signature at the bottom of a list. earlier in
the year i already tried to add a link and i could not do it - but i
admit that is a much more difficult task in the mobile app.
the german links:
* sign here: https://de.wikipedia.org/wiki/Wikipedia:Offener_Brief_an_die_Mitglieder_des…
just as a side note, up to know this page collected close to 4'000 signatures.
We just released our new WMDE fundraising report. See the detailed
There is also an executive summary of the report on the movement blog:
>From € 700,00 to € 8,200,000 in less than five years. That is an
astonishing development. But fundraising is not just about money.
Fundraising at Wikimedia Deutschland, and across the entire Wikimedia
movement, not only helps us achieve financial goals, it also helps raise
awareness for our mission. We reach several million people each day
during our fundraising campaign in Germany, making ours the most
successful online campaign in the country. With the help of a systematic
strategy and comprehensive A/B tests, we have managed to increase our
annual fundraising campaign revenue by more than ten times in just five
years. This success is the result of a data-driven approach that focuses
primarily on donors and their behavior.
This Fundraising Report reviews the findings gathered from our latest
campaign and assesses how our work has developed over recent years.
Thanks to extensive A/B tests and the technical infrastructure that we
have built up over the years, we are constantly and systematically
collecting data and insights. This allows us to analyze the behavior and
payment methods of donors, which in turn helps us to plan and
continually improve our campaigns. We have identified five main factors
that contribute towards fundraising success at Wikimedia Deutschland,
and this report discusses them in detail.
*Five factors of successful banners*
1. Relevance: No association, no donation. Our results show that a
personal appeal in banners, the use of key words, and particularly
references to current events make our appeals more relevant and
therefore more persuasive to potential donors.
2. Visibility is something one has to fight hard for. The time span we
have in which to draw attention to our message is very short. This
Fundraising Report presents findings relating to when is the best time
for the banner to appear and analyzes various design decisions,
including color scheme.
3. Closer to the reader: If there is one thing that the entire donation
process should be–from reading the appeal through to completing a
donation – it’s straightforward. The fewer clicks required, the better.
This fact is nothing new, and it certainly does not only apply to us,
but this report will explain the concrete application of this knowledge
in the creation of successful banners.
4. Donation obstacles should be kept to a minimum. Two findings in
particular have emerged from our previous years’ work: Firstly,
including suggested donation amounts on the banner has proven to provide
effective guidance for donors. The lower the sum, the higher the number
of people who donate–and the overall success of a campaign is greater
when more donors give smaller amounts. Secondly, the option to donate
anonymously is very important to many donors.
5. Raising the campaign profile: It pays to communicate fundraising
goals and show the progress of donations. In 2014 in particular we saw
how effective the creation of dramatic moments within a campaign can be.
This report also touches on a surprising topic: the principle of “social
proof” demonstrates how the behavior of a group can motivate others to
act in the same way, yet Wikimedia Deutschland’s fundraising campaign
made good use of the reverse of this effect.
Looking back, the five factors all played a crucial role in the success
of our campaigns; and looking ahead, their importance for the
international movement stretches far beyond monetary matters. We should
all see fundraising as the start of a relationship – one that requires
continuous care and attention.
*Fundraising is not about banners only*
Our goal for the future is to persuade donors to become long-term
supporters of free knowledge and the Wikimedia movement. This report
provides a glimpse into our strategy on how to maintain and consolidate
our donor relationships, which are built on three main pillars: regular
contact, targeted appeals, and personal dialogue–all things that are not
possible through communication via banners alone. This report discusses
the enormous benefits that stand to be gained from attracting long-term
support for the Wikimedia mission.
Using the example of donation certificates, this report will show how we
benefit from taking the wishes and expectations of donors seriously. Our
postal and electronic mailings are proof of how target-group-specific
content and communication strategies can ensure long-term success. The
fundamental importance of a well-functioning customer service team
should also not be overlooked. During the last fundraising campaign in
Germany, for example, we received hundreds of calls and answered well in
excess of 5,000 e-mails. Contact is therefore not merely an additional
service; it is the very basis of future relationships.
Looking ahead to future challenges, the report ends with a call to
intensify donor relationships, to focus on donors’ needs, and to further
diversify fundraising communications.
(see the detailed report here:
Mit freundlichen Grüßen
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Telefon 030 - 219 158 26 -19
Stellen Sie sich eine Welt vor, in der jeder Mensch freien Zugang zu der Gesamtheit des Wissens der Menschheit hat. Helfen Sie uns dabei! http://spenden.wikimedia.de/
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