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The August 2020 issue of the Wikimedia Research Newsletter is out
by Mohammed Sadat Abdulai 13 Sep '20

13 Sep '20

The August 2020 issue of the Wikimedia Research Newsletter is out: https://meta.wikimedia.org/wiki/Research:Newsletter/2020/August In this issue: 1. "Protecting the Web from Misinformation" by detecting Wikipedia spammers and identifying pages to protect 2. Editors successfully signal their intelligence by writing high-quality articles - but only when contributing non-anonymously 3. Briefly *** 11 recent publications were covered or listed in this issue *** Masssly and Tilman Bayer --- Wikimedia Research Newsletter https://meta.wikimedia.org/wiki/Research:Newsletter/ * Follow us on Twitter: @WikiResearch <http://twitter.com/Wikiresearch> * Like us on Facebook: Facebook.com/WikiResearch/ * Receive this newsletter by mail: Research-newsletter Mailing List - Wikimedia <https://lists.wikimedia.org/mailman/listinfo/research-newsletter>

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WikiHist.html: English Wikipedia's Full Revision History in HTML Format
by Robert West 13 Sep '20

13 Sep '20

Hi all, *TL;DR:* So far, Wikipedia's full revision history has been available only in wiki markup, not in HTML -- a big limitation for researchers. We are changing this by releasing WikiHist.html, Wikipedia's full history (up until March 2019) in HTML: https://zenodo.org/record/3605388 <https://t.co/ZhK7kKaPCi?amp=1> Caveat emptor: 7 TB! Tweet: https://twitter.com/cervisiarius/status/1301791239558311936 *More details:* Wikipedia is written in the wikitext markup language. When serving content, the MediaWiki software that powers Wikipedia parses wikitext to HTML, thereby inserting additional content by expanding macros (templates and modules). Hence, researchers who intend to analyze Wikipedia as seen by its readers should work with HTML, rather than wikitext. Since Wikipedia’s revision history is made publicly available by the Wikimedia Foundation exclusively in wikitext format, researchers have had to produce HTML themselves, typically by using Wikipedia’s REST API for ad-hoc wikitext-to-HTML parsing. This approach, however, (1) does not scale to very large amounts of data and (2) does not correctly expand macros in historical article revisions. We have solved these problems by developing a parallelized architecture for parsing massive amounts of wikitext using local instances of MediaWiki, enhanced with the capacity of correct historical macro expansion. By deploying our system, we produce and hereby release WikiHist.html, English Wikipedia’s full revision history in HTML format. It comprises the HTML content of 580M revisions of 5.8M articles generated from the full English Wikipedia history spanning 18 years from 1 January 2001 to 1 March 2019. Boilerplate content such as page headers, footers, and navigation sidebars are not included in the HTML. For more details, please refer to https://zenodo.org/record/3605388 <https://t.co/ZhK7kKaPCi?amp=1> and to the dataset paper: Blagoj Mitrevski, Tiziano Piccardi, and Robert West: WikiHist.html: English Wikipedia’s Full Revision History in HTML Format. In *Proceedings of the 14th International AAAI Conference on Web and Social Media,* 2020. https://arxiv.org/abs/2001.10256 Best regards, Bob

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DBpedia Autumn Hackathon, starting Sept 21st
by Sebastian Hellmann 10 Sep '20

10 Sep '20

Apologies for cross-posting Dear DBpedians, Linked Data savvies and Ontologists, We would like to invite you to join the DBpedia Autumn Hackathon 2020 as a new format to contribute to DBpedia, gain fame, win small prizes and experience the latest technology provided by DBpedia Association members. The hackathon is part of the Knowledge Graphs in Action conference on October 6, 2020. Please check here: https://wiki.dbpedia.org/meetings/KnowledgeGraphsInAction # Timeline * Registration of participants - main communication channel will be the #hackathon channel in DBpedia Slack (sign up https://dbpedia-slack.herokuapp.com/, then add yourself to the channel). If you wish to receive a reminder email on Sep 21st, you can leave your email address in this form: https://tinyurl.com/y24ps5jt * Until September 14th - preparation phase, participating organisations prepare details, track formation, additional tracks can be proposed, please contact dbpedia-events(a)infai.org <mailto:dbpedia-events@infai.org> * September 21st - Announcement of details for each track, including prizes, participating data, demos, tools and tasks. Check updates on hackathon website https://wiki.dbpedia.org/events/dbpedia-autumn-hackathon-2020 * September 21st to October 1st - hacking period, coordinated via DBpedia slack * October 1st, 23:59 Hawaii Time - Submission of hacking result (3 min video and 2-3 paragraph summary with links, if not stated otherwise in the track) * October 5th, 16:00 CEST - Final Event, each track chair presents a short recap of the track, announces prizes or summarizes the result of hacking. * October 6th, 9:50 - 15:30 CEST - Knowledge Graphs in Action Event * Results and videos are documented on the DBpedia Website and the DBpedia Youtube channel. # Member Tracks The member tracks are hosted by DBpedia Association members, who are technology leaders in the area of Knowledge Engineering. Additional tracks can be proposed until Sep 14th, please contact dbpedia-events(a)infai.org <mailto:dbpedia-events@infai.org>. * timbr SQL Knowledge Graph: Learn how to model, map and query ontologies in timbr and then model an ontology of GDELT, map it to the GDELT database, and answer a number of questions that currently are quite impossible to get from the BigQuery GDELT database. Cash prizes planned. https://www.timbr.ai/ * GNOSS Knowledge Graph Builder: Give meaning to your organisation’s documents and data with a Knowledge Graph. https://www.gnoss.com/en/products/semantic-framework * ImageSnippets: Labeling images with semantic descriptions. Use DBpedia spotlight and an entity matching lookup to select DBpedia terms to describe images. Then explore the resulting dataset through searches over inference graphs and explore the ImageSnippets dataset through our SPARQL endpoint. Prizes planned. http://www.imagesnippets.com * Diffbot: Build Your Own Knowledge Graph! Use the Natural Language API to extract triples from natural language text and expand these triples with data from the Diffbot Knowledge Graph (10+ billion entities, 1+ trillion facts). Check out the demo http://demo.nl.diffbot.com/. All participants will receive access to the Diffbot KG and tools for (non-commercial) research for one year ($10,000 value). # Dutch National Knowledge Graph Track Following the DBpedia FlexiFusion approach, we are currently flexi-fusing a huge, dbpedia-style knowledge graph that will connect many Linked Data sources and data silos relevant to the country of the Netherlands. We hope that this will eventually crystallize a well-connected sub-community linked open data (LOD) cloud in the same manner as DBpedia crystallized the original LOD cloud with some improvements (you could call it LOD Mark II). Data and hackathon details will be announced on 21st of September. # Improve DBpedia Track A community track, where everybody can participate and contribute in improving existing DBpedia components, in particular the extraction framework, the mappings, the ontology, data quality test cases, new extractors, links and other extensions. Best individual contributions will be acknowledged on the DBpedia website by anointing the WebID/Foaf profile. (chaired by Milan Dojchinovski and Marvin Hofer from the DBpedia Association & InfAI and the DBpedia Hacking Committee) # DBpedia Open Innovation Track (not part of the hackathon, pre-announcement) For the DBpedia Spring Event 2021, we are planning an Open Innovation Track, where DBpedians can showcase their applications. This endeavour will not be part of the hackathon as we are looking for significant showcases with development effort of months & years built on the core infrastructure of DBpedia such as the SPARQL endpoint, the data, lookup, spotlight, DBpedia Live, etc. Details will be announced during the Hackathon Final Event on October 5. (chaired by Heiko Paulheim et al.) Stay tuned and stay safe! With kind regards, The DBpedia Organizing-Team

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Upcoming WMF/Research-Team Office hours on September 1st, 2020
by Martin Gerlach 01 Sep '20

01 Sep '20

Hi all, Join the Research Team at the Wikimedia Foundation [1] for their monthly Office hours on 2020-09-01 at 16.00-17.00 (UTC). Through these office hours, we aim to make ourselves more available to answer some of the research related questions that you as Wikimedia volunteer editors, organizers, affiliates, staff, and researchers face in your projects and initiatives (*). To participate, join the video-call via this Wikimedia-meet link [2]. There is no set agenda - feel free to add your item to the list of topics in the etherpad [3] (You can do this after you join the meeting, too.), otherwise you are welcome to also just hang out. More detailed information (e.g. about how to attend) can be found here [4]. Started in the beginning of 2020 as an experiment [5], after the first 6 editions we have evaluated the scope and format of the Research office hours. In order to decrease barriers of accessibility and to facilitate more direct interaction, we have switched the format from IRC to video call. We will re-evaluate the current format at the end of the year. We would also be glad to hear your feedback and/or comments. (*) Some example cases we hope to be able to support you in: - You have a specific research related question that you suspect you should be able to answer with the publicly available data and you don’t know how to find an answer for it, or you just need some more help with it. For example, how can I compute the ratio of anonymous to registered editors in my wiki? - You run into repetitive or very manual work as part of your Wikimedia contributions and you wish to find out if there are ways to use machines to improve your workflows. These types of conversations can sometimes be harder to find an answer for during an office hour, however, discussing them can help us understand your challenges better and we may find ways to work with each other to support you in addressing it in the future. - You want to learn what the Research team at the Wikimedia Foundation does and how we can potentially support you. Specifically for affiliates: if you are interested in building relationships with the academic institutions in your country, we would love to talk with you and learn more. We have a series of programs that aim to expand the network of Wikimedia researchers globally and we would love to collaborate with those of you interested more closely in this space. - You want to talk with us about one of our existing programs [6]. Hope to see many of you, Martin (WMF Research Team) [1] https://research.wikimedia.org/team.html [2] https://meet.wmcloud.org/ResearchOfficeHours [3] https://etherpad.wikimedia.org/p/Research-Analytics-Office-hours [4] https://www.mediawiki.org/wiki/Wikimedia_Research/Office_hours [5] https://lists.wikimedia.org/pipermail/wiki-research-l/2019-December/007039.… [6] https://research.wikimedia.org/projects.html -- Martin Gerlach Research Scientist Wikimedia Foundation

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Number of registered editors per country
by Thomas Stieve 24 Aug '20

24 Aug '20

Dear all, Hope all is well. Does anyone know of published statistics for the number of registered editors per country? I need it for 2016, but any year close to that would suffice. Your help is greatly appreciated, Tom -- Thomas Stieve Ph.D. Candidate School of Geography and Development University of Arizona

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Upcoming Research Newsletter: New Papers Open For Review (August 2020)
by Mohammed Sadat Abdulai 23 Aug '20

23 Aug '20

Hi everyone, We’re preparing for the August 2020 research newsletter and looking for contributors. Please take a look at https://etherpad.wikimedia.org/p/WRN202008 and add your name next to any paper you are interested in covering. Our target publication time is 30 August 15:59 UTC. If you can't make this deadline but would like to cover a particular paper in the subsequent issue, leave a note next to the paper's entry below. As usual, short notes and one-paragraph reviews are most welcome. *Highlights from this month:* - Broadening African Self-Representation on Wikipedia: A Field Experiment - Characterizing Online Vandalism: A Rational Choice Perspective - Commonsense Knowledge in Wikidata - Impact of individual actions on the collective response of social systems - Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages - Notable Site Recognition using Deep Learning on Mobile and Crowd-sourced Imagery - Protecting the Web from Misinformation - Ripples on the web: Spreading lake information via Wikipedia - Successful Online Socialization: Lessons from the Wikipedia Education Program - Wikipedia, COVID-19, and readers' interests across languages - Wikipedia, The Free Online Medical Encyclopedia Anyone Can Plagiarize: Time to Address Wiki-Plagiarism - WiTPy: A Toolkit to Parse and Analyse Wikipedia Talk Pages Masssly and Tilman Bayer [1] http://meta.wikimedia.org/wiki/Research:Newsletter [2] WikiResearch (@WikiResearch) | Twitter <https://twitter.com/WikiResearch>

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[Events] WikiCred Tech Demo Hour September 10, 12pm ET
by Ahmed Medien 21 Aug '20

21 Aug '20

Announcement: September 10 Zoom Webinar Wiki Credibility Tech Demo Hour The WikiCred grants initiative was launched earlier this year with a focus on information credibility/reliability and new tools on open-knowledge platforms like Wikipedia and Wikidata. The Demo Hour will be held on September 10th at 12 pm EDT where 6 of our grantees will demo their Wikipedia projects. You can register for the online event here <https://docs.google.com/forms/d/e/1FAIpQLSeEpva_wwZA9xIjtTni7-y0tZ_VgXW8nzV…> . 👈👈 WikiCred is a grants programme managed by the Credibility Coalition, Hacks Hackers, members of Wikimedia DC, and other groups. We support research, software projects, and Wikimedia events that explore information reliability and credibility in the Wikimedia space and the overall online information ecosystem. So far, we have funded 12 projects over 3 rounds of funding. You can find a full list of the projects here <http://wikicred.org/#projects> or our own blog <https://misinfocon.com/search?q=wikicred>. Projects range from strengthening credible vaccine content on Wikipedia to automating the additions of references to Wikidata. 6 grantees will join us to present their work for 5 mins each followed by a Q&A from the attendees. Let me know if you have any questions about the project or the event. Ahmed & WikiCred Team wikicred.org Partners <https://www.wikicred.org/#who-we-are> / Projects <http://wikicred.org/#projects> / Funders <http://wikicred.org/#funders>

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[Wikimedia Research Showcase] August 19, 2020: Readership and Navigation
by Janna Layton 19 Aug '20

19 Aug '20

Hi all, The next Research Showcase will be live-streamed on Wednesday, August 19, at 9:30 AM PDT/16:30 UTC, and will be on the theme of readership and navigation. YouTube stream: https://www.youtube.com/watch?v=MeUl0zjHdF8 As usual, you can join the conversation on IRC at #wikimedia-research. You can also watch our past research showcases here: https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase This month's presentations: What matters to us most and why? Studying popularity and attention dynamics via Wikipedia navigation data. By Taha Yasseri (University College Dublin), Patrick Gildersleve (Oxford Internet Institute) While Wikipedia research was initially focused on editorial behaviour or the content to a great extent, soon researchers realized the value of the navigation data both as a reflection of readers interest and, more generally, as a proxy for behaviour of online information seekers. In this talk we will report on various projects in which we utilized pageview statistics or readers navigation data to study: movies financial success [1], electoral popularity [2], disaster triggered collective attention [3] and collective memory [4], general navigation patterns and article typology [5], and attention patterns in relation to news breakouts. - [1] Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data. PLoS One (2013). https://doi.org/10.1371/journal.pone.0071226 - [2] Wikipedia traffic data and electoral prediction: towards theoretically informed models. EPJ Data Science (2016). https://doi.org/10.1140/epjds/s13688-016-0083-3 - [3] Dynamics and biases of online attention: the case of aircraft crashes. Royal Society Open Science (2016). https://doi.org/10.1098/rsos.160460 - [4] The memory remains: Understanding collective memory in the digital age. Science Advances (2018). https://doi.org/10.1126/sciadv.1602368 - [5] Inspiration, captivation, and misdirection: Emergent properties in networks of online navigation. Springer (2018). https://ora.ox.ac.uk/objects/uuid:73baed3c-d3fe-4200-8e90-2d80b11f21cf Query for Architecture, Click through Military. Comparing the Roles of Search and Navigation on Wikipedia By Dimitar Dimitrov (GESIS - Leibniz Institute for the Social Sciences) As one of the richest sources of encyclopedic information on the Web, Wikipedia generates an enormous amount of traffic. In this paper, we study large-scale article access data of the English Wikipedia in order to compare articles with respect to the two main paradigms of information seeking, i.e., search by formulating a query, and navigation by following hyperlinks. To this end, we propose and employ two main metrics, namely (i) searchshare -- the relative amount of views an article received by search --, and (ii) resistance -- the ability of an article to relay traffic to other Wikipedia articles -- to characterize articles. We demonstrate how articles in distinct topical categories differ substantially in terms of these properties. For example, architecture-related articles are often accessed through search and are simultaneously a "dead end" for traffic, whereas historical articles about military events are mainly navigated. We further link traffic differences to varying network, content, and editing activity features. Lastly, we measure the impact of the article properties by modeling access behavior on articles with a gradient boosting approach. The results of this paper constitute a step towards understanding human information seeking behavior on the Web. - Different Topic, Different Traffic: How Search and Navigation Interplay on Wikipedia. Journal of Web Science (2019). https://doi.org/10.34962/jws-71 -- Janna Layton (she/her) Administrative Associate - Product & Technology Wikimedia Foundation <https://wikimediafoundation.org/>

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Help spreading the word about our research
by Shani Evenstein 17 Aug '20

17 Aug '20

Dear WikiFriends, I'm hoping you & yours are all well, safe and healthy in these unprecedented times we have all found ourselves in. I'm writing you today with my 'educator & researcher' hat on, with a special request to help Piotr Konieczny & I spread the word about a new global research we are conducting. While using Wikimedia-related assignments (Wikipedia, Commons, WikiBooks, WikiSource, Wikidata, Wiktionary etc) in the classroom has been used all over the world for over a decade, very little research was conducted about what instructors who have tried it actually think about the experience. We are hoping that answering the questions in the survey will help us better understand: - Whether this teaching approach is effective (or not) - What are some of the challenges experienced by instructors - How the process could be improved The questions are meant for any instructors running a wiki assignment, whether it is in k-12 or higher education, formal or informal educational setting. We are hoping the results will allow us to globally share experiences and learn from one another, so we can make it smoother, easier and more effective for educators joining these efforts. It is important to note that this would be the first time (that we know of!) that an academic research of this type has been conducted around the world, so we really need your help in spreading the word about it in your local communities. We're hoping that any of you, supporting such initiatives around the world over the years, would forward it to your local Education contacts and ask them to participate. The more instructors participating, the better. We realize that it would have been great to have the questionnaire in a variety of languages, but in order for us to process the data properly and not via third-party translations and keep the anonymity and privacy of participants, it was decided to release the survey just in English. Here is a link to the survey - https://tinyurl.com/yd6dfata <https://l.facebook.com/l.php?u=https%3A%2F%2Ftinyurl.com%2Fyd6dfata%3Ffbcli…> . Thank you all in advance, and of course, if there are any questions, Piotr & I are here. Stay healthy & safe! Shani. ----------------------------------------------- *Shani Evenstein Sigalov* * Lecturer, Tel Aviv University. * EdTech Innovation Strategist, NY/American Medical Program, Sackler School of Medicine, Tel Aviv University. * PhD Candidate, School of Education, Tel Aviv University. * Azrieli Foundation Research Fellow. * OER & Emerging Technologies Coordinator, UNESCO Chair <https://education.tau.ac.il/node/3495> on Technology, Internationalization and Education, School of Education, Tel Aviv University <https://education.tau.ac.il/node/3495>. * Member of the Board of Trustees <https://wikimediafoundation.org/profile/shani-evenstein-sigalov/>, Wikimedia Foundation <https://wikimediafoundation.org/>. * Chairperson, The Hebrew Literature Digitization Society <http://www.israelgives.org/amuta/580428621>. * Chief Editor, Project Ben-Yehuda <http://benyehuda.org>. +972-525640648

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Attribution for pageviews API
by workPostings 17 Aug '20

17 Aug '20

Hi, I have a question regarding wikimedia's pageviews API. I'm going to use this API (example: https://wikimedia.org/api/rest_v1/metrics/pageviews/top/en.wikipedia/all-ac…), <https://wikimedia.org/api/rest_v1/metrics/pageviews/top/en.wikipedia/all-ac…>on commercial use, but I don't find instructions on which license it's based on. I'm also going to filter some of the results (i.e. showing only athletes from Europe, things like that). So the question regards the license of that API. I want to attribute it correctly. Appreciate your help

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