Hi everyone,
We’re preparing for the May 2020 research newsletter and looking for contributors. Please take a look at https://etherpad.wikimedia.org/p/WRN202005 and add your name next to any paper you are interested in covering. Our target publication date is May 31, 2020 18:00 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:
- A Deeper Investigation of the Importance of Wikipedia Links to the Success of Search Engines
- A Large-scale Study of Wikipedia Users' Quality of Experience
- Adding evidence of the effects of treatments into relevant Wikipedia pages: a randomised trial
- Analyzing Wikipedia Users’ Perceived Quality Of Experience: A Large-Scale Study
- Beyond Performing Arts: Network Composition and Collaboration Patterns
- Citation Detective: a Public Dataset to Improve and Quantify Wikipedia Citation Quality at Scale
- Collaboration of Open Content News in Wikipedia: The Role and Impact of Gatekeepers
- Content Growth and Attention Contagion in Information Networks: Addressing Information Poverty on Wikipedia
- Detecting Undisclosed Paid Editing in Wikipedia
- Diagnosing Incompleteness in Wikidata with The Missing Path
- Domain-Specific Automatic Scholar ProfilingBased on Wikipedia
- How Wikipedia disease information evolve over time? An analysis of disease-based articles changes
- Knowledge Graphs on the Web -- an Overview
- Layered Graph Embedding for Entity Recommendation using Wikipedia in the Yahoo! Knowledge Graph
- Lexemes in Wikidata: 2020 status
- Mapping Wikipedia
- Matching Ukrainian Wikipedia Red Links with English Wikipedia’s Articles
- Measuring Social Bias in Knowledge Graph Embeddings
- Multi-class Multilingual Classification of Wikipedia Articles Using Extended Named Entity Tag Set
- Novel version of PageRank, CheiRank and 2DRank for Wikipedia in Multilingual Network using Social Impact
- Situating Wikipedia as a health information resource in various contexts: A scoping review
- The Political Geography of Shoah Knowledge and Awareness, Estimated from the Analysis of Global Library Catalogues and Wikipedia User Statistics
- The Positioning Matters: Estimating Geographical Bias in the Multilingual Record of Biographies on Wikipedia
- The Subversive Potential of Wikipedia: A Resource for Diversifying Political Science Content Online
- Vandalism Detection in Crowdsourced Knowledge Bases
- Visual Narratives and Collective Memory across Peer-Produced Accounts of Contested Sociopolitical Events
- Visualising open communities. Guidelines from three case studies
- WAC: A Corpus of Wikipedia Conversations for Online Abuse Detection
- Wikigender: A Machine Learning Model to Detect Gender Bias in Wikipedia
- WikiHist.html: English Wikipedia's Full Revision History in HTML Format
Masssly and Tilman Bayer
[1] http://meta.wikimedia.org/wiki/Research:Newsletter[2] WikiResearch (@WikiResearch) | Twitter
*The First Wikidata Workshop*
Co-located with the 19th International Conference on Semantic Web (ISWC
2020).
Date: To be announced (late October, early November)
The workshop will be held online, afternoon European time.
Website: https://wikidataworkshop.github.io/
== Important dates ==
Papers due: August 10, 2020
Notification of accepted papers: September 11, 2020
Camera-ready papers due: September 21, 2020
Workshop date: To be announced (end October/early November)
== Overview ==
Wikidata is an openly available knowledge base, hosted by the Wikimedia
Foundation. It can be accessed and edited by both humans and machines and
acts as a common structured-data repository for several Wikimedia projects,
including Wikipedia, Wiktionary, and Wikisource. It is used in a variety of
applications by researchers and practitioners alike.
In recent years, we have seen an increase in the number of publications
around Wikidata. While there are several dedicated venues for the broader
Wikidata community to meet, none of them focuses on publishing original,
peer-reviewed research. This workshop fills this gap - we hope to provide a
forum to build this fledgling scientific community and promote novel work
and resources that support it.
The workshop seeks original contributions that address the opportunities
and challenges of creating, contributing to, and using a global,
collaborative, open-domain, multilingual knowledge graph such as Wikidata.
We encourage a range of submissions, including novel research, opinion
pieces, and descriptions of systems and resources, which are naturally
linked to Wikidata and its ecosystem, or enabled by it. What we’re less
interested in are works which use Wikidata alongside or in lieu of other
resources to carry out some computational task - unless the work feeds back
into the Wikidata ecosystem, for instance by improving or commenting on
some Wikidata aspect, or suggesting new design features, tools and
practices.
We welcome interdisciplinary work, as well as interesting applications
which shed light on the benefits of Wikidata and discuss areas of
improvement.
The workshop is planned as an interactive half-day event, in which most of
the time will be dedicated to discussions and exchange rather than frontal
presentations. For this reason, all accepted papers will be presented in
short talks and accompanied by a poster. We are considering online options
in response to ongoing challenges such as travel restrictions and the
recent Covid-19 pandemic.
== Topics ==
Topics of submissions include, but are not limited to:
- Data quality and vandalism detection in Wikidata
- Referencing in Wikidata
- Anomaly, bias, or novelty detection in Wikidata
- Algorithms for aligning Wikidata with other knowledge graphs
- The Semantic Web and Wikidata
- Community interaction in Wikidata
- Multilingual aspects in Wikidata
- Machine learning approaches to improve data quality in Wikidata
- Tools, bots and datasets for improving or evaluating Wikidata
- Participation, diversity and inclusivity aspects in the Wikidata ecosystem
- Human-bot interaction
- Managing knowledge evolution in Wikidata
== Submission guidelines ==
We welcome the following types of contributions.
- Full research paper: Novel research contributions (7-12 pages)
- Short research paper: Novel research contributions of smaller scope than
full papers (3-6 pages)
- Position paper: Well-argued ideas and opinion pieces, not yet in the
scope of a research contribution (6-8 pages)
- Resource paper: New dataset or other resource directly relevant to
Wikidata, including the publication of that resource (8-12 pages)
- Demo paper: New system critically enabled by Wikidata (6-8 pages)
Submissions must be as PDF or HTML, formatted in the style of the Springer
Publications format for Lecture Notes in Computer Science (LNCS). For
details on the LNCS style, see Springer’s Author Instructions.
The papers will be peer-reviewed by at least two researchers. Accepted
papers will be published as open access papers on CEUR (we only publish to
CEUR if the authors agree to have their papers published).
Papers have to be submitted through easychair:
https://easychair.org/conferences/?conf=wikidataworkshop2020
== Proceedings ==
The complete set of papers will be published with the CEUR Workshop
Proceedings (CEUR-WS.org).
== Organizing committee ==
- Lucie-Aimée Kaffee, University of Southampton
- Oana Tifrea-Marciuska, Bloomberg
- Elena Simperl, King’s College London
- Denny Vrandečić, Google AI
== Programme committee ==
- Lydia Pintscher, Wikidata, Wikimedia Deutschland
- Maria-Esther Vidal, TIB Hannover
- Miriam Redi, Wikimedia Foundation
- Edgar Meij, Bloomberg
- Simon Razniewski, Max Planck Institute for Informatics
- Alessandro Piscopo, BBC
- Pavlos Vougiouklis, Huawei Technologies, Edinburgh
- Marco Ponza, University of Pisa
- Markus Krötzsch, Technische Universität Dresden
- Andrew D. Gordon, Microsoft Research & University of Edinburgh
- Cristina Sarasua, University of Zurich
- Aidan Hogan, Universidad de Chile
- Claudia Müller-Birn, FU Berlin
- Finn Årup Nielsen, Technical University of Denmark
--
Lucie-Aimée Kaffee
The WMF Research team has published a new pageview report of inbound
traffic coming from Facebook, Twitter, YouTube, and Reddit.[1]
The report contains a list of all articles that received at least 500 views
from one or more of these platforms (i.e. someone clicked a link on Twitter
that sent them directly to a Wikipedia article). The report is available
on-wiki and will be updated daily at around 14:00 UTC with traffic counts
from the previous calendar day.
We believe this report provides editors with a valuable new information
source. Daily inbound social media traffic stats can help editors monitor
edits to articles that are going viral on social media sites and/or are
being linked to by the social media platform itself in order to fact-check
disinformation and other controversial content[2][3].
The social media traffic report also contains additional public article
metadata that may be useful in the context of monitoring articles that are
receiving unexpected attention from social media sites, such as...
- the total number of pageviews (from all sources) that article received
in the same period of time
- the number of pageviews the article received from the same platform
(e.g. Facebook) the previous day (two days ago)
- the number of editors who have the page on their watchlist
- the number of editors who have watchlisted the page AND recently
visited it
We want your feedback! We have some ideas of our own for how to improve the
report, but we want to hear yours! If you have feature suggestions, please
add them here.[4] We intend to maintain this daily report for at least the
next two months. If we receive feedback that the report is useful, we are
considering making it available indefinitely.
If you have other questions about the report, please first check out our
(still growing) FAQ [5]. All questions, comments, concerns, ideas, etc. are
welcome on the project talkpage on Meta.[4]
1. https://en.wikipedia.org/wiki/User:HostBot/Social_media_traffic_report
2.
https://www.engadget.com/2018/03/15/wikipedia-unaware-would-be-youtube-fact…
3.
https://mashable.com/2017/10/05/facebook-wikipedia-context-articles-news-fe…
4.
https://meta.wikimedia.org/wiki/Research_talk:Social_media_traffic_report_p…
5.
https://meta.wikimedia.org/wiki/Research:Social_media_traffic_report_pilot/…
Cheers,
Jonathan
--
Jonathan T. Morgan
Senior Design Researcher
Wikimedia Foundation
User:Jmorgan (WMF) <https://meta.wikimedia.org/wiki/User:Jmorgan_(WMF)>
(Uses He/Him)
*Please note that I do not expect a response from you on evenings or
weekends*
Hi all,
The next Research Showcase will be live-streamed on Wednesday, May 20, at
9:30 AM PDT/16:30 UTC.
This month we will learn about recent research on machine learning systems
that rely on human supervision for their learning and optimization -- a
research area commonly referred to as Human-in-the-Loop ML. In the first
talk, Jie Yang will present a computational framework that relies on
crowdsourcing to identify influencers in Social Networks (Twitter) by
selectively obtaining labeled data. In the second talk, Estelle Smith will
discuss the role of the community in maintaining ORES, the machine learning
system that predicts the quality in Wikipedia applications.
YouTube stream: https://www.youtube.com/watch?v=8nDiu2ebdOI
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:
*OpenCrowd: A Human-AI Collaborative Approach for Finding Social
Influencers via Open-Ended Answers Aggregation*
By: Jie Yang, Amazon (current), Delft University of Technology (starting
soon)
Finding social influencers is a fundamental task in many online
applications ranging from brand marketing to opinion mining. Existing
methods heavily rely on the availability of expert labels, whose collection
is usually a laborious process even for domain experts. Using open-ended
questions, crowdsourcing provides a cost-effective way to find a large
number of social influencers in a short time. Individual crowd workers,
however, only possess fragmented knowledge that is often of low quality. To
tackle those issues, we present OpenCrowd, a unified Bayesian framework
that seamlessly incorporates machine learning and crowdsourcing for
effectively finding social influencers. To infer a set of influencers,
OpenCrowd bootstraps the learning process using a small number of expert
labels and then jointly learns a feature-based answer quality model and the
reliability of the workers. Model parameters and worker reliability are
updated iteratively, allowing their learning processes to benefit from each
other until an agreement on the quality of the answers is reached. We
derive a principled optimization algorithm based on variational inference
with efficient updating rules for learning OpenCrowd parameters.
Experimental results on finding social influencers in different domains
show that our approach substantially improves the state of the art by 11.5%
AUC. Moreover, we empirically show that our approach is particularly useful
in finding micro-influencers, who are very directly engaged with smaller
audiences.
Paper: https://dl.acm.org/doi/fullHtml/10.1145/3366423.3380254
*Keeping Community in the Machine-Learning Loop*
By: C. Estelle Smith, MS, PhD Candidate, GroupLens Research Lab at the
University of Minnesota
On Wikipedia, sophisticated algorithmic tools are used to assess the
quality of edits and take corrective actions. However, algorithms can fail
to solve the problems they were designed for if they conflict with the
values of communities who use them. In this study, we take a
Value-Sensitive Algorithm Design approach to understanding a
community-created and -maintained machine learning-based algorithm called
the Objective Revision Evaluation System (ORES)—a quality prediction system
used in numerous Wikipedia applications and contexts. Five major values
converged across stakeholder groups that ORES (and its dependent
applications) should: (1) reduce the effort of community maintenance, (2)
maintain human judgement as the final authority, (3) support differing
peoples’ differing workflows, (4) encourage positive engagement with
diverse editor groups, and (5) establish trustworthiness of people and
algorithms within the community. We reveal tensions between these values
and discuss implications for future research to improve algorithms like
ORES.
Paper:
https://commons.wikimedia.org/wiki/File:Keeping_Community_in_the_Loop-_Unde…
--
Janna Layton (she, her)
Administrative Assistant - Product & Technology
Wikimedia Foundation <https://wikimediafoundation.org/>
The April 2020 issue of the Wikimedia Research Newsletter is out:
https://meta.wikimedia.org/wiki/Research:Newsletter/2020/April
In this issue:
1 What is trending on (which) Wikipedia?2 Briefly3 Other recent publications3.1 "Automatically Neutralizing Subjective Bias in Text"3.2 "Neural Based Statement Classification for Biased Language"3.3 Dissertation about data quality in Wikidata3.4 Nineteenth-century writers important for Russian Wiktionary3.5 "Online Disinformation and the Role of Wikipedia"3.6 "Assessing the Factual Accuracy of Generated Text"3.7 "Revision Classification for Current Events in Dutch Wikipedia Using a Long Short-Term Memory Network"3.8 "DBpedia FlexiFusion: the Best of Wikipedia > Wikidata > Your Data"3.9 "Improving Neural Question Generation using World Knowledge"3.10 Concurrent "epistemic regimes" feed disagrements among Wikipedia editors3.11 "ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia"
- *** 12 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
* Like us on Facebook: Facebook.com/WikiResearch/
* Receive this newsletter by mail: Research-newsletter Mailing List - Wikimedia
Forwarding.
Pine
( https://meta.wikimedia.org/wiki/User:Pine )
---------- Forwarded message ---------
From: Bridges, Laurie <laurie.bridges(a)oregonstate.edu>
Date: Fri, May 8, 2020 at 9:10 AM
Subject: [libraries] CFP. Wikipedia and Academic Libraries: A Global Project
To: libraries(a)lists.wikimedia.org <libraries(a)lists.wikimedia.org>
Call for Chapter Proposals – Due date June 1.
Project title: Wikipedia and Academic Libraries: A Global Project
Editors: Laurie M. Bridges, Raymond Pun, Roberto Arteaga
OA Publisher: Maize Books, an imprint of Michigan Publishing
License: CC BY 4.0
Email: WikiGlobalProject(a)gmail.com
Website: https://sites.google.com/view/globalwikipedia/
Proposals due: June 1, 2020
Notifications sent by: June 30, 2020
Send proposals as MS Word Document to: WikiGlobalProject(a)gmail.com
Questions: WikiGlobalProject(a)gmail.com
Project Information
This open access edited volume will be a collection of approximately
20 chapters authored by academic library workers and faculty, Library
and Information Science (LIS) faculty, and disciplinary faculty from
around the globe that highlights engagement with Wikimedia-related
projects and activities. This volume will be divided into two
sections, and possibly a third: The first section will include
real-world examples of activities and approaches to working with
Wikipedia. The second section will focus on the theories and
underlying concepts required for the development of pedagogical
approaches to teaching with and within Wikipedia. A third thematic
section may be added, depending on the breadth and number of
submissions, for example, a section related specifically to Wikidata.
Possible Topics
We are seeking chapters that include both practical and theoretical
work. Possible topics for chapters include (but are not limited to)
the following list:
Case studies of Wikipedia in information literacy instruction
Student researchers in Wikipedia
Collaboration between Wikimedia user groups and academic library staff
Wikipedia student clubs and their connection to libraries
Benefits of academic libraries partnering with Wikimedia projects
The role of Wikimedians/Wikipedians in Residence
Collaborating with university faculty in the classroom
Edit-a-thon pedagogy and practice
Critical Librarianship and Wikipedia
Wikipedia's fight against misinformation and "fake news"
Medical students and training
Use of Wikibooks in classes
Wikidata visualizations for education
Increasing and diversifying the audience for archival collections
through Wikipedia
Addressing gaps in Wikipedia, such as gender, LGBTQ+, racial,
linguistic, regional, etc.
Submission Information
Please send the following information to the editors by June 1, 2020:
A tentative title and abstract proposal: Up to 500 words in MS Word
describing what you would intend to submit for this book. In your
abstract, indicate which section of the book your proposal is aligned
to.
Please include links to any other publications you may have (i.e. an
article, a blog post, or anything else that best reflects your writing
style)
Author CVs or resumes (no more than 2 pages)
Information for Accepted Proposals
Final chapters will be approximately 3,000 words in length. All
citations must be APA 7th edition. This OA publication will be
licensed under a CC BY 4.0 license. After final chapters have been
edited and approved in English, authors will have the option of
providing a second-language translation of their chapter. (example:
English and Basque or English and Yoruba).This will be determined on a
case by case basis.
April 1 – June 1, 2020: Call for chapter proposals is distributed
June 30, 2020: Chapter proposals selected and authors notified
October 1, 2020: First draft of chapters due to editors
December 1, 2020: Second draft of chapters due to editors
January 1, 2021: Manuscript to publisher
______________________________
Remote working hours (PST): M-Th, 8 am – 1 pm, 7 pm – 10 pm; F 9 am – 5 pm
Make an appointment (Zoom)
Keybase app: LaurieBridges
Laurie Bridges
Instruction and Outreach Librarian / Associate Professor
Oregon State University
OSU Libraries and Press
+1.541.737.8821
Library liaison to:
School of Writing, Literature, and Film
School of Arts and Communication
INTO OSU
_______________________________________________
Libraries mailing list
Libraries(a)lists.wikimedia.org
https://lists.wikimedia.org/mailman/listinfo/libraries
Forwarding.
Pine
( https://meta.wikimedia.org/wiki/User:Pine )
---------- Forwarded message ---------
From: Clifford Snow <clifford(a)snowandsnow.us>
Date: Sat, Apr 25, 2020 at 8:06 PM
Subject: [Talk-us] OSM Foundation’s Call for Microgrant Applications
To: talk-us <talk-us(a)openstreetmap.org>
In case you missed this announcement, I'm reposting it on talk-us mailing list.
2020 will be the first year that the OSM Foundation operates the new
microgrants project. In the coming weeks, we hope to hear from you
about a bold, community-driven, and impactive OpenStreetMap project
idea that will benefit from a microgrant of up to 5000 euros. We
welcome a broad range of projects, with the minimum requirement being
a clear connection to OpenStreetMap.
What is a microgrant? In our case, it is a modest amount of funds
awarded to applicants in order to fund direct expenses of a project.
For an idea of successful projects, you can take a look at the
Humanitarian OpenStreetMap Team’s 2019 microgrant awardees. Keep in
mind that the OSMF has a wider focus than the humanitarian sector,
spanning our global community, and welcomes applications with any
focus that relates to OpenStreetMap. We particularly encourage
applicants to consider the core values from the OSMF’s mission
statement and how any microgrant work can incorporate them.
The OSMF Microgrant Program focuses on simple grant proposals, and we
will swiftly decide on what to fund. Our goal is to avoid a
complicated and long application and decision process. You should
submit a brief and concise proposal, and we plan to quickly announce
the awardees.
We encourage submissions from individuals, groups, and organizations
who have a clear idea they want to pursue. Each project should be
completed within 12 months of the microgrant being awarded this
spring. Microgrants are open to all OSMF members, and can be submitted
in any language. If you are not yet a member of OSMF then you can
apply to join up until the time you submit a microgrant application,
and be eligible for an award. Please note there is a fee waiver
program that may allow you to join the OSMF at no cost.
In light of the ongoing health crisis regarding COVID19, we will not
be awarding microgrants for projects which require offline group
gatherings and in person meetings, although these ideas are certainly
valuable for future rounds.
Funding can be used for a variety of purposes. You may need tools and
supplies for mapping activity, funds for training materials,
technology expenses for a series of virtual mapathons, prizes for an
online coding, mapping, or writing contest, and many more examples.
Please embrace your own creativity and not feel limited by the range
of examples.
We encourage you to consult with your local OpenStreetMap community
when planning a microgrant application, and make sure you adhere to
community guidelines in the scope of the project. If accepted for a
microgrant, you will be responsible for reporting progress, signing a
grant agreement, and making sure to follow the detailed microgrant
rules. It is strongly suggested that your project uses the funding to
enable volunteer work to have a wider and stronger impact than it
would without funding.
The call for microgrants will open on April 19th, 2020 and we will
continue to accept applications through May 10th, 2020. In order to
submit, visit the OSM Wiki page and click on “Start your application”
to enter the template. When this is complete, send a message to
microgrants at osmfoundation.org. We also encourage sharing your
application on osmf-talk when it is submitted. If you need help with
the submission process, please feel free to contact the Microgrants
Committee for help. If you don’t have enough time to prepare your plan
and application, please consider submitting it in a possible future
round of microgrants.
Once the submission period closes on May 10th, we invite the community
to review the complete list of submissions and provide feedback on the
wiki page. We also will accept feedback by email to microgrants at
osmfoundation.org and via osmf-talk.
Complete timeline:
April 19: call for microgrant applications opens
May 10: final date for submission (23:59 Pacific Time Zone, USA).
May 10-TBD: community feedback period
Late May: announcement of awards
For more details, see the complete rules and guidelines on the OSM
wiki and contact us at microgrants at osmfoundation.org with any
questions. This is the first time the OSMF is sponsoring such an
activity, and we look forward to learning together about how this
benefits our community and how to build a transparent, effective, and
inclusive microgrants program for everyone involved. We are grateful
for the opportunity to make funds available to the community and hope
to hear your ideas in the coming weeks.
Clifford
Member of the OSMF Microgrants Committee
--
@osm_washington
www.snowandsnow.us
OpenStreetMap: Maps with a human touch
_______________________________________________
Talk-us mailing list
Talk-us(a)openstreetmap.org
https://lists.openstreetmap.org/listinfo/talk-us
Hi all,
join us for our monthly Analytics/Research Office hours on 2020-04-29 at
18.00-19.00 (UTC). Bring all your research questions and ideas to discuss
projects, data, analysis, etc… To participate, please join the IRC channel:
#wikimedia-research [1]. More detailed information can be found here [2] or
on the etherpad [3] if you would like to add items to agenda or check notes
from previous meetings.
Note that for this edition the timeslot has slightly changed in order to
avoid conflicts with other events (i.e. moved to one hour later in the day
and one week later in the month than originally announced).
Best,
Martin
[1] irc://chat.freenode.net:6667/wikimedia-research
[2] https://www.mediawiki.org/wiki/Wikimedia_Research/Office_hours
[3] https://etherpad.wikimedia.org/p/Research-Analytics-Office-hours
--
Martin Gerlach
Research Scientist
Wikimedia Foundation
Hi everyone,
We’re preparing for the April 2020 research newsletter and looking for contributors. Please take a look at https://etherpad.wikimedia.org/p/WRN202004 and add your name next to any paper you are interested in covering. Our target publication date is 25 April 23:59 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:
- Adding evidence of the effects of treatments into relevant Wikipedia pages: a randomised trial
- How Wikipedia disease information evolve over time? An analysis of disease-based articles changes
- Mapping Wikipedia
- Measuring Social Bias in Knowledge Graph Embeddings
- Situating Wikipedia as a health information resource in various contexts: A scoping review
- The Political Geography of Shoah Knowledge and Awareness, Estimated from the Analysis of Global Library Catalogues and Wikipedia User Statistics
- Vandalism Detection in Crowdsourced Knowledge Bases
- Visual Narratives and Collective Memory across Peer-Produced Accounts of Contested Sociopolitical Events
- Visualising open communities. Guidelines from three case studies
- What is Trending on Wikipedia? Capturing Trends and Language Biases Across Wikipedia Editions
Masssly and Tilman Bayer
[1] http://meta.wikimedia.org/wiki/Research:Newsletter[2] WikiResearch (@WikiResearch) | Twitter
Hi everyone,
We are delighted to announce that Wiki Workshop 2020 will be held in
Taipei on April 20 or 21, 2020 (the date to be finalized soon) and as
part of the Web Conference 2020 [1]. In the past years, Wiki Workshop
has traveled to Oxford, Montreal, Cologne, Perth, Lyon, and San
Francisco.
You can read more about the call for papers and the workshops at
http://wikiworkshop.org/2020/#call. Please note that the deadline for
the submissions to be considered for proceedings is January 17. All
other submissions should be received by February 21.
If you have questions about the workshop, please let us know on this
list or at wikiworkshop(a)googlegroups.com.
Looking forward to seeing you in Taipei.
Best,
Miriam Redi, Wikimedia Foundation
Bob West, EPFL
Leila Zia, Wikimedia Foundation
[1] https://www2020.thewebconf.org/