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
(this is an announcement in my capacity as a volunteer.)
Inspired by a lightning talk at the recent CEE Meeting by our colleague
Lars Aronsson, I made a little command-line tool to automate batch
recording of pronunciations of words by native speakers, for uploading to
Commons and integration into Wiktionary etc. It is called *pronuncify*, is
written in Ruby and uses the sox(1) tool, and should work on any modern
Linux (and possibly OS X) machine. It is available here, with
I was then asked about a Windows version, and agreed to attempt one. This
version is called *pronuncify.net <http://pronuncify.net>*, and is a .NET
gooey GUI version of the same tool, with slightly different functions. It
is available here, with instructions.
Both tools require word-list files in plaintext, with one word (or phrase)
per line. Both tools name the files according to the standard established
in [[commons:Category:Pronunciation]], and convert them to Ogg Vorbis for
you, so they are ready to upload.
In the future, I may add OAuth-based direct uploading to Commons. If you
run into difficulties, please file issues on GitHub, for the appropriate
tool. Feedback is welcome.
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).
this is my first post to this list. I think Wikipedia is a great project
and am impressed by how well it works. It seems the (lack of) funding of
the project is one of the more severe threats to its continued success.
Since (I assume) the biggest cost is the maintenance of servers, I wonder
if there are there any plans of making Wikipedia decentralised.
Let me elaborate. I'm thinking of a system where many users each would
store a small part of the encyclopedia. A user wanting to look up or edit
an article connects to another user who has a copy of that article. When an
article is updated the update is sent to all other users (that are online)
responsible for storing that article.
Are there any efforts to accomplish this? Would it be feasible?
At Wikidata we often find issues with data imported from a Wikipedia. Lists
have been produced with these issues on the Wikipedia involved and arguably
they do present issues with the quality of Wikipedia or Wikidata for that
matter. So far hardly anything resulted from such outreach.
When Wikipedia is a black box, not communicating about with the outside
world, at some stage the situation becomes toxic. At this moment there are
already those at Wikidata that argue not to bother about Wikipedia quality
because in their view, Wikipedians do not care about its own quality.
Arguably known issues with quality are the easiest to solve.
There are many ways to approach this subject. It is indeed a quality issue
both for Wikidata and Wikipedia. It can be seen as a research issue; how to
deal with quality and how do such mechanisms function if at all.
I blogged about it..
As you may have heard, I joined the Wikimedia Foundation last Monday as the
VP of Human Resources. I am so excited to be here and help to the best of
One of the projects that I am currently focusing on is adding two members
to our board of trustees. I wanted to reach out to you and ask you to
nominate candidates that you think should be considered.
I am attaching a role description that will provide more insight into what
the ideal candidates for these two board slots would be. If someone you
know comes to mind, please send the name of the candidate including some
information regarding why you think they would be great. Also let me know
if you know that person is interested in the position and can afford the
time commitment the role will require or if it’s someone you think may be
great but are unsure if they are interested or would have time to commit.
Please email nominations to board-nominations(a)lists.wikimedia.org by next
Wednesday, Sept 30th. I understand that this is a short notice and not much
time to nominate, but we need to find someone that can start in Nov and we
need to contact, screen, interview, etc before then.
Thank you in advance for your nominations and have a wonderful weekend!
At some point of time, the best you could do is to reach for a
superstition and hope it will work. It doesn't matter how it will be
explained after, but at this point of time, it's only that
superstition which matters.
My particular superstition is that Brane would be able to see his
eulogy and that we'll be able to laugh together. You know, it's a rare
opportunity to see how your eulogy would look like, so I hope I am
giving it to him.
An hour ago I heard that he is in critical condition. At first, I was
thinking what should I write after he dies. Then, I realized that I
should write it now and post it after. Then, it's come into my mind
that I should send it immediately as, at least, I could think about
reading with him this eulogy and your comments after he recovers.
Since August 2014 he is struggling with bone cancer. His curse is that
his body is so strong, that chemotherapy is not working yet.
Paradoxically, we hope that his body is weak enough now that it will
finally accept chemotherapy. Monday would be crucial day for him.
He is one of those "invisible" Wikimedians who actually contributed
significantly to our movement. Some of you, mostly those who visited
Belgrade, know him.
He is one of the founders of Wikimedia Serbia. It's a pity that he is
in this condition while WMRS is preparing to celebrate its 10th
anniversary. Here is our photo from the founding assembly .
Presently, he is a board member of Wikimedia Serbia.
His epic fight for copyright correctness on Serbian Wikipedia created
the foundations of the present day strict copyright rules. It's a
great achievement for a project of such size and it was possible just
because of him.
While he was active editor, he was highly trusted Wikipedian and he
was administrator, bureaucrat and checkuser on Serbian Wikipedia, as
well as on a number of of other projects in Serbian language.
Alpha software for transliteration between Cyrillic and Latin scripts
of Serbian language in MediaWiki was his work. That was the basis for
the future implementation. It was the first software of that kind
implemented in one web engine.
He is my close friend. Besides a lot of things which he did, which
will be mentioned at appropriate time, I want to say that many things
which I did wouldn't be possible without his contribution.
He is now very exhausted and he won't be able to read this today or
tomorrow. However, I am sure he will be able to read it on Monday,
after he recovers a bit. So, your support matters, no matter of my
superstitious reasons for sending this email.