Wikimedia-l May 2018

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96 participants
62 discussions

[Foundation-l] Improving search in Wikipedia through quality and concept discovery
by Brian J Mingus 09 Sep '22

09 Sep '22

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…>

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[Foundation-l] Fwd: 18.1831, All: Call for Participation: Wikipedia Volunteers
by GerardM 09 Aug '22

09 Aug '22

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

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Re: [Wikimedia-l] Politics
by Bill Takatoshi 25 Apr '20

25 Apr '20

>>> 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. -Will

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Fresh data on the gender gap in content
by Asaf Bartov 10 Feb '20

10 Feb '20

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

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Recognition of Wikimedia Community User Group Albania
by Kirill Lokshin 26 Feb '19

26 Feb '19

Hi everyone! I'm very happy to announce that the Affiliations Committee has recognized [1] Wikimedia Community User Group Albania [2] as a Wikimedia User Group. The group aims to improve content about Albania across the Wikimedia projects, including Commons and Wikidata, and to collaborate with other Wikimedia user groups, chapters, and other free culture groups in Albania and across the region. Please join me in congratulating the members of this new user group! Regards, Kirill Lokshin Chair, Affiliations Committee [1] https://meta.wikimedia.org/wiki/Affiliations_Committee/Resolutions/Recognit… [2] https://meta.wikimedia.org/wiki/Wikimedia_Community_User_Group_Albania

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Why We Read Wikipedia in your language
by Leila Zia 06 Feb '19

06 Feb '19

Hi all, ==Background== 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 languages.:) ==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 at https://meta.wikimedia.org/wiki/Research:Characterizing_Wikipedia_Reader_Be… (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.) Best, Leila -- Leila Zia Senior Research Scientist Wikimedia Foundation

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English Fundraiser Launch - Tues 28th November
by Joseph Seddon 27 Nov '18

27 Nov '18

Hey all! I wanted to send a quick reminder that our English language fundraiser is officially launching tomorrow afternoon (Tuesday 28th November, at 16.00 UTC) with some final systems tests running between now and then. ---Banners and Ideas--- You can see the all of our current most effective fundraising banners on our Fundraising Ideas page where you can also contribute any specific ideas or stories we should tell via social media, banners, emails etc: https://meta.wikimedia.org/wiki/Fundraising/2017-18_Fundraising_ideas ---Blog Posts--- We've recently published two blog posts about our fundraising work. The first covers how we try to limit the disruption to our readers during campaigns. The second is a recent tranche of research conducted into what our readers think about our fundraising. Take a look! Banner limiting: https://blog.wikimedia.org/2017/10/03/fundraising-banner-limit/ Donor research: https://blog.wikimedia.org/2017/11/17/fundraising-donor-learnings/ ---Reporting Issues--- If you see any technical issues with the banners or payments systems please do report it on phabricator: https://phabricator.wikimedia.org/maniphest/task/create/?template=118862 If you see a donor on a talk page, OTRS, or social media with questions about donating or having difficulties in the donation process, please refer them to: donate{{at}}wikimedia.org Here is also the ever present fundraising IRC channel to raise urgent technical issues: #wikimedia-fundraising http://webchat.freenode.net?channels=%23wikimedia-fundraising&uio=d4 <http://webchat.freenode.net/?channels=%23wikimedia-fundraising&uio=d4> ---Next Updates--- There will be a further launch announcement on the Wikimedia blog tomorrow and I will give a brief update at the end of the week with our progress and hopefully some interesting initial lessons learnt. A more substantial update will follow later in the week. Finally, I’d like to thank the community here in advance for your help and patience over the coming weeks. From here on out, wish us luck! Many Thanks -- Seddon Community & Audience Engagement Associate Advancement (Fundraising), Wikimedia Foundation

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Gendergap approach causing problems
by Romaine Wiki 18 Nov '18

18 Nov '18

Hi all, On Wikipedia and in our movement we are aware of the gendergap that exists and all kinds of activities are organised to make the gap smaller. I think this is great as no single gap should exist in collecting all the knowledge in the world, as well as our movement should be diverse as the world's population is diverse. The statistics are clear on this matter, this is something to take care of. However, a part of the approach is causing problems, because general statistics should not be applied on individuals as that reduces humans to numbers only. The reason why I bring this up is because I recently received an e-mail from a user in the Wikimedia movement who has (temporarily?) stopped contributing as she is not happy with a specific aspect of the atmosphere in Wikimedia. She does not speak out at loud, but I think we must be aware as movement of the silent cry, therefore this e-mail to bring awareness (but with respect for the privacy of this individual). What has happened? She was invited to participate in a Wikimedia activity, because: 1. she is a woman 2. she is from a minority 3. she is from an area in the world with much less editors (compared to Europe/US) and perhaps also because her colour of her skin is a bit different then mine (Caucasian). At the same time she has the impression that the work she does on the Wikimedia wiki('s) is not valued, nor taken into account. She does not want to be invited because she is a woman, nor because she is from a minority, nor ....... etc. This is offensive. She only wants to be invited because of the work she contributes on Wikipedia/etc. Besides the many good initiatives and intentions, this kind of approaches to our contributors is demotivating them, please be aware of this. I believe demotivation/frustration is the largest problem we face as movement. I heard from people that the problem described is called tokenism <https://en.wikipedia.org/wiki/Tokenism>. I believe the only way to close the gaps related to gender, minorities, etc, is to create an atmosphere in what everyone is appreciated for what she/he is doing, completely unrelated to the gender someone appears to have, the ethnicity, race, area of the world, etc etc etc etc. Thank you! Romaine

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convert from BitCoin to FoldingCoin and other proofs of useful work
by James Salsman 02 Nov '18

02 Nov '18

The Foundation has been accepting BitCoin donations. Unfortunately, BitCoin is very wasteful in terms of electricity, and is therefore a dirty cryptocurrency. I recommend that the Foundation immediately cease accepting BitCoin, and require donors who wish to donate in cryptocurrency to convert to FoldingCoin instead. Please see: FoldingCoin (FLDC) http://foldingcoin.net/ whitepaper: https://docs.google.com/document/d/1y4MV9AwGLTRFqD-kjC4uN0AX59kHOpO1OWsabnx… This conversion will place the Foundation at the forefront of cryptocurrency technology, and stop it from contributing to extremely dirty waste. As other cryptocurrencies based on proofs of useful work instead of useless work emerge, the Foundation should consider those. FoldingCoin is based on proofs of useful prediction of protein folding, which is useful for computer-aided antibody design, and used in turn for cancer therapies and many other applied and research medical fields. I also invite anyone in the community interested in co-authoring my forthcoming derivative whitepaper on proofs of useful intelligibility remediation work to contact me off-list, please. I am also willing to help with proofs of useful encyclopedia article improvement, but I am not certain if ORES is yet robust enough to support such proof in a secure fashion. Best regards, Jim Salsman

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Information on "Multiple failed attempts to log in" emails
by John Bennett 25 Aug '18

25 Aug '18

Hello, Many of you may have been receiving emails in the last 24 hours warning you of "Multiple failed attempts to log in" with your account. I wanted to let you know that the Wikimedia Foundation's Security team is aware of the situation, and working with others in the organization on steps to decrease the success of attacks like these. The exact source is not yet known, but it is not originating from our systems. That means it is an external effort to gain unauthorized access to random accounts. These types of efforts are increasingly common for websites of our reach. A vast majority of these attempts have been unsuccessful, and we are reaching out personally to the small number of accounts which we believe have been compromised. While we are constantly looking at improvements to our security systems and processes to offset the impact of malicious efforts such as these, the best method of prevention continues to be the steps each of you take to safeguard your accounts. Because of this, we have taken steps in the past to support things like stronger password requirements,[1] and we continue to encourage everyone to take some routine steps to maintain a secure computer and account. That includes regularly changing your passwords,[2] actively running antivirus software on your systems, and keeping your system software up to date. My team will continue to investigate this incident, and report back if we notice any concerning changes. If you have any questions, please contact the Support and Safety team (susa{{(a)}}wikimedia.org). John Bennett Director of Security, Wikimedia Foundation [1] https://meta.wikimedia.org/wiki/Password_strength_requirements [2] https://meta.wikimedia.org/wiki/Special:ChangePassword

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