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"
http://youtube-global.blogspot.com/2009/09/five-stars-dominate-ratings.html…
I think a sane, well researched (with actual subjects) rating system
is
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.
PDF<http://grey.colorado.edu/mediawiki/sites/mingus/images/6/68/DeHoustMangalat…>
- Rassbach, L., Mingus., B, Blackford, T. (2007). *Exploring the
feasibility of automatically rating online article quality*. Technical
Report. PDF<http://grey.colorado.edu/mediawiki/sites/mingus/images/d/d3/RassbachPincock…>
Hoi,
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...
Thanks,
GerardM
---------- 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
To: LINGUIST(a)listserv.linguistlist.org
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
<reviews(a)linguistlist.org>
Homepage: http://linguistlist.org/
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
http://linguistlist.org/LL/posttolinguist.html
===========================Directory==============================
1)
Date: 18-Jun-2007
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
Dear subscribers,
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
at:
http://linguistlist.org/donation/fund-drive2007/wikipedia/index.cfm.
The speed with which we met our goal, thanks to the interest and generosity
of
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
more
leisure time, we are hoping that you will be able to help us get started on
the
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
as
"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
articles;
*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
efforts.
We hope you are as enthusiastic about this effort as we are. Just to help us
all
get started looking at Wikipedia more critically, and to easily identify an
area
needing improvement, we suggest that you take a look at the List of
Linguists
page at:
http://en.wikipedia.org/wiki/List_of_linguists. M
Many people are not listed there; others need to have more facts and
information
added. If you would like to participate in this exciting update effort,
please
respond by sending an email to LINGUIST Editor Hannah Morales at
hannah(a)linguistlist.org, suggesting what your role might be or which
linguistics
entries you feel should be updated or added. Some linguists who saw our
campaign
on the Internet have already written us with specific suggestions, which we
will
share with you soon.
This update project will take major time and effort on all our parts. The
end
result will be a much richer internet resource of information on the breadth
and
depth of the field of linguistics. Our efforts should also stimulate
prospective
students to consider studying linguistics and to educate a wider public on
what
we do. Please consider participating.
Sincerely,
Hannah Morales
Editor, Wikipedia Update Project
Linguistic Field(s): Not Applicable
-----------------------------------------------------------
LINGUIST List: Vol-18-1831
Hullo everyone.
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[1] 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,
here:
https://meta.wikimedia.org/wiki/User:Ijon/Content_gap
(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
coverage.)
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[2] 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. :)
A.
[1] https://query.wikidata.org/
[2] Yay #100wikidays :) https://meta.wikimedia.org/wiki/100wikidays
--
Asaf Bartov
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!
https://donate.wikimedia.org
Being put together by Eliezer Yudkowsky of LessWrong. Content is
cc-by-sa 3.0, don't know about the software.
https://arbital.com/p/arbital_ambitions/
Rather than the "encyclopedia" approach, it tries to be more
pedagogical, teaching the reader at their level.
Analysis from a sometime Yudkowsky critic on Tumblr:
http://nostalgebraist.tumblr.com/post/140995096534/a-year-ago-i-remember-be…
(there's a pile more comments linked from the notes on that post,
mostly from quasi-fans; I have an acerbic comment in there, but you
should look at the site yourself first.)
No idea if this will go anywhere, but might be of interest; new
approaches generally are. They started in December, first publicised
it a week ago and have been scaling up. First day it collapsed due to
load from a Facebook post announcement ... so maybe hold off before
announcing it everywhere :-)
- d.
This is probably of interest to this list.
https://wikimediafoundation.org/wiki/Delegation_of_policy-making_authority
---
Delegation of policy-making authority
This was approved on December 13, 2016 by the Board of Trustees.
Whereas, the Board of Trustees has traditionally approved certain global
Wikimedia Foundation policies (such as the Privacy Policy and Terms of
Use) as requested during the July 4, 2004 Board meeting
<https://wikimediafoundation.org/wiki/Meetings/July_4,_2004>;
Whereas, the Wikimedia Foundation Executive Director has authority to
conduct the affairs of the Wikimedia Foundation, which includes adopting
and implementing policies;
Resolved, the Board hereby delegates the authority to adopt, alter, and
revoke policies to the Executive Director, who may further delegate such
authority to Wikimedia Foundation staff as they deem appropriate;
Resolved, the Board may continue to review and approve policies for the
Wikimedia Foundation upon request to the Executive Director or as required
by law.
Approve
Christophe Henner (Chair), Maria Sefidari (Vice Chair), Dariusz
Jemielniak, Kelly Battles, Guy Kawasaki, Jimmy Wales, Nataliia Tymkiv,
and Alice Wiegand
---
I wonder how much of this resolution is formalizing what was already
happening and how much of this is moving the Wikimedia Foundation in a new
direction. After a very tumultuous year at the Wikimedia Foundation, this
is certainly a notable development.
I also wonder in what ways this abrupt change will alter the relationship
between the editing communities and the Board of Trustees. The Wikimedia
Foundation Board of Trustees seems to be committing itself to downsizing
its role and responsibilities. The concern is that a change like this will
reduce accountability when policies are set, unset, and changed by someone
overseeing a large staff that regularly comes in conflict with an even
larger set of editing communities. The Executive Director, of course, is
unelected and has been a central point of repeated controversies recently.
It's been less than a year since the previous Executive Director resigned
after being forced out by her staff. In the context of the recent history,
this resolution is all the more puzzling.
MZMcBride
Hello, everyone.
(this is an announcement in my capacity as a volunteer.)
Inspired by a lightning talk at the recent CEE Meeting[1] 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[2], with
instructions.
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[3], 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.
A.
[1]
https://meta.wikimedia.org/wiki/Wikimedia_CEE_Meeting_2015/Programme/Lightn…
[2] https://github.com/abartov/pronuncify
[3] https://github.com/abartov/Pronuncify.net
--
Asaf Bartov
I was very glad that the Foundation decided to extend the fundraiser.
I think adding projects outside of the lengthy, formulaic,
overly-committee laden, but necessary in part FDC funding process and
getting a head start on the endowment is essential for retaining the
soul of the Foundation's traditional agility and creativity. Sure, it
made a liar out of Jimmy and other officials this year, and they
should be commended by those of us who think the effective
non-sacrifice to their reputations is worth it.
Accordingly, I propose the following $2.5 million-range projects for
further extension of this year's fundraiser:
1. A study of systemic bias in economics articles on the English Wikipedia;
2. An extension of the (in the interest of full disclosure: my student
and my) Accuracy Review of Wikipedias Google Summer of Code Project
into a general computer-aided educational system including authentic
intelligibility remediation of spoken language skills, as proposed at
https://goo.gl/WGUIFa
3. A study of the top five endowment-grade mutual funds available for
general Foundation investments, their prospects, and opportunities for
divestments and strategic investments consistent with the Mission
broadly construed.
4. A study of the social implications of copyright law and regulation
changes in relation to the Foundation's Mission for the Public Policy
group.
That's about $10 million. What other ideas are there?
Best regards,
Jim
Kaya
Some of you would have become aware of a project in Perth Western Australia
that has been ongoing since 2014. The ultimate aim is have nys.wikipedia.org
currently its at https://incubator.wikimedia.org/wiki/Wp/nys with 500
articles
While everyone has been focused on enjoying the holiday break the people
facilitating this project have been busily writing a report on the project
and it was publish last night.
It looks at working with an Indigenous cultural/language group in the
southwest of Western Australia, the first chapter covers this detail.
The project has been working on a number of very specific challenges facing
minority and Indigenous cultures in contributing to the projects. It
discusses what worked how that evolved, we investigated intangible
knowledge sources and even challenged the methods of collecting the
statistics behind the conclusion that Noongar language is a threatened
language.
The project has worked with multiple generations of Nyoongar people in
differing environments, its worked with students from the early years of
primary school 6,7 8 years old through to post graduate students.
Wikimedia Australia is currently organising opportunities to discuss with
facilitators of the project, the first event is in Darwin in March and
later in Perth during October. As always if you find yourself in Perth let
me know we are always ready to have yarn. In the mean time enjoy reading
about Noongarpedia and we hope it offers insights
http://cultural-science.org/journal/index.php/culturalscience
--
G
ideon
President Wikimedia Australia
WMAU: http://www.wikimedia.org.au/wiki/User:Gnangarra
Photo Gallery: http://gnangarra.redbubble.com