Hi all,
I joined the WMF Research team in June, 2021 as the Senior Research
Community Officer. Over the last two years, I have had the pleasure of
interacting with many of you through Office Hours, Research Showcases, the
Research Fund, and the listening tour I held during my first few months. I
have enjoyed learning more about your research interests, involvement in
the broader Wikimedia community, and how you think the Foundation can
increase its support for your work. With your input, we were able to
publish a vision and strategy
<https://meta.wikimedia.org/wiki/Research:Research_Community_Vision_and_Stra…>
for the community that will guide our efforts in the coming years.
I am writing to let you know that April 21st will be my last day at the
Wikimedia Foundation. I am moving to another organization where I will
continue to build my experience in community management and supporting open
research practices.
I want to thank you for the energy and enthusiasm that you bring to your
work. I particularly want to acknowledge those of you who have presented
your research at Showcases and Wiki Workshop, reviewed abstracts and grant
proposals, and applied to the Research Fund. The success of these
initiatives is due in a large part to your thoughtful contributions.
Warm regards,
Emily
--
Emily Lescak (she / her)
Senior Research Community Officer
The Wikimedia Foundation
Hi all,
The next Research Showcase, with the theme of Images on Wikipedia, will be
live-streamed Wednesday, April 19, at 16:30 UTC. Find your local time here
<https://zonestamp.toolforge.org/1681921857>.
YouTube stream: https://www.youtube.com/watch?v=vW0waU-QArU
You can join the conversation on IRC at #wikimedia-research or on the
YouTube chat.
This month's presentations:
A large scale study of reader interactions with images on WikipediaBy *Daniele
Rama, University of Turin*Wikipedia is the largest source of free
encyclopedic knowledge and one of the most visited sites on the Web. To
increase reader understanding of the article, Wikipedia editors add images
within the text of the article’s body. However, despite their widespread
usage on web platforms and the huge volume of visual content on Wikipedia,
little is known about the importance of images in the context of free
knowledge environments. To bridge this gap, we collect data about English
Wikipedia reader interactions with images during one month and perform the
first large-scale analysis of how interactions with images happen on
Wikipedia. First, we quantify the overall engagement with images, finding
that one in 29 pageviews results in a click on at least one image, one
order of magnitude higher than interactions with other types of article
content. Second, we study what factors associate with image engagement and
observe that clicks on images occur more often in shorter articles and
articles about visual arts or transports and biographies of less well-known
people. Third, we look at interactions with Wikipedia article previews and
find that images help support reader information need when navigating
through the site, especially for more popular pages. The findings in this
study deepen our understanding of the role of images for free knowledge and
provide a guide for Wikipedia editors and web user communities to enrich
the world’s largest source of encyclopedic knowledge.
- Paperː
https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-021-0…
Visual gender biases in Wikipediaː A systematic evaluation across the ten
most spoken languagesBy *Pablo Beytia, Catholic University of Chile*The
existing research suggests a significant gender gap in Wikipedia
biographical articles, with a minimal representation of women and gender
asymmetries in the textual content. However, the visual aspects of this gap
(e.g., image volume and quality) have received little attention. This study
examined asymmetries between women's and men's biographies, exploring
written and visual content across the ten most widely spoken languages. The
cross-lingual analysis reveals that (1) the most salient male biases appear
when editors select which personalities should have a Wikipedia page, (2)
the trends in written and visual content are dissimilar, (3) male
biographies tend to have more images across languages, and (4) female
biographies have better visual quality on average. The open database of
this study provides eight indicators of gender asymmetries in ten
occupational domains and ten languages. That information allows for a
granular view of gender biases, as well as exploring more macroscopic
phenomena, such as the similarity between Wikipedia versions according to
their gender bias structures.
- Papersː
Beytía, P., Agarwal, P., Redi, M., & Singh, V. K. (2022). Visual Gender
Biases in Wikipedia: A Systematic Evaluation across the Ten Most Spoken
Languages. Proceedings of the International AAAI Conference on Web and
Social Media, 16(1), 43-54. https://doi.org/10.1609/icwsm.v16i1.19271https://ojs.aaai.org/index.php/ICWSM/article/view/19271Beytía, P. & Wagner,
C. (2022). Visibility layers: a framework for systematizing the gender gap
in Wikipedia content. Internet Policy Review, 11(1).
https://doi.org/10.14763/2022.1.1621https://policyreview.info/articles/analysis/visibility-layers-framework-sys…
You can watch our past Research Showcases here:
https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
Hope you can join us!
Warm regards,
Emily
--
Emily Lescak (she / her)
Senior Research Community Officer
The Wikimedia Foundation
Sending this again from my current address. Left Gmail a long time ago -- not sure the redirect still works... My apologies if this is hitting your inbox twice!
_ _ _ _
Dear Wikimedia research community,
I'd have a question for the data savvy people on this list :)
My goal is simple: for a sample of English Wikipedia editors, I'm trying to identify their edits which were reverted. I can see two possible way of doing this:
1. Identify the reverts using the SHA1 values. (A revert happens when the edit exactly restores the page to its previous state.)
2. Identify the reverts using the "undo" button.
As I see it, solution 2 is less "precise" (you'll miss some reverts, e.g., those performed manually). However, it would also be less computationally intensive, and I don't see that it would introduce any bias (results can be compared across editors in a statistical model).
However, I do not see the information about whether a revision was reverted using the “undo” button in the enwiki database: https://www.mediawiki.org/w/index.php?title=Manual:Database_layout/diagram&…
I find this surprising. Am I missing something? (And if so, how do you personally feel about strategy 1 vs. strategy 2?)
Thank you so much for any insight you might be willing to provide! :D
Sincerely,
Jérôme
Hi all,
We are excited to invite you to the *10th edition* of Wiki Workshop on *May
11, 2023 *(starting 12:00 UTC).
We are putting an engaging program for this year's special edition. Thanks
to many of you, we have received more than 60 research submissions, the
largest in the history of Wiki Workshop. :) We are gradually posting
content on https://wikiworkshop.org/2023/ but until then:
We hope that you decide to join us for this year's edition. *To register*:
Please go to (privacy statement for pretix [0])
https://pretix.eu/wikimedia/wikiworkshop2023/ . This year's event is free
of charge and held virtually.
We look forward to connecting with many of you on May 11th.
Best,
Leila, on behalf of Wiki Workshop 2023 organizers [1]
[0]
https://foundation.wikimedia.org/wiki/Legal:Wiki_Workshop_Privacy_Statement
[1] https://wikiworkshop.org/2023/#organization
+++ apologies for cross postings +++
TWO JOB OPENINGS
1. PhD Studentship in Social Statistics
2. Postdoc / Research Scientist in the Kinship Inequalities Research Group
1. Jointly Funded Studentship
PhD Studentship in Social Statistics
University of Manchester &
Max Planck Institute for Demographic Research (MPIDR)
Application Deadline: 14th of May 2023
We are pleased to invite applications to a 3.5-year University of Manchester doctoral studentship in Social Statistics. The studentship is jointly funded by the Social Statistics Department, University of Manchester, UK, and the Max Planck Institute for Demographic Research (MPIDR), Germany, one of the world-leading research centres in population sciences. The studentship will be part of the International Max Planck Research School for Population, Health and Data Science (IMPRS-PHDS) imprs-phds.mpg.de
(Shortened text. See full text on our website: www.demogr.mpg.de/go/phd-in-social-statistics<http://www.demogr.mpg.de/go/phd-in-social-statistics>)
Contact:
For informal enquiries about the position, please contact
* Arkadiusz Wiśniowski (a.wisniowski(a)manchester.ac.uk<mailto:a.wisniowski@manchester.ac.uk>),
* Emilio Zagheni (zagheni(a)demogr.mpg.de<mailto:zagheni@demogr.mpg.de>), or
* Kingsley Purdam (Kingsley.Purdam(a)manchester.ac.uk<mailto:Kingsley.Purdam@manchester.ac.uk>).
2. OPPORTUNITY FOR POSTDOCS
Postdoc / Research Scientist in the
Kinship Inequalities Research Group
Max Planck Institute for Demographic Research (MPIDR)
Application Deadline: 15th of May 2023
The Max Planck Institute for Demographic Research (MPIDR) is recruiting one highly qualified postdoctoral researcher within the Kinship Inequalities Research Group. The position is offered for three years. This group, led by Diego Alburez-Gutierrez, studies how differences in kinship among persons and groups determine individual outcomes and shape social structures. It aims to bring together experts from areas like Demography, Sociology, Anthropology, Mathematics, Statistics, Computer Science, Biology, etc. to advance the subfield of kinship demography and address pressing scientific and societal questions.
(Shortened text. See full text on our website: https://www.demogr.mpg.de/go/postdoc-kinship-inequalities)
Contact:
For enquiries about the position, please contact alburezgutierrez(a)demogr.mpg.de<mailto:alburezgutierrez@demogr.mpg.de>
Follow us on Twitter: @MPIDRnews
--
This mail has been sent through the MPI for Demographic Research. Should you receive a mail that is apparently from a MPI user without this text displayed, then the address has most likely been faked. If you are uncertain about the validity of this message, please check the mail header or ask your system administrator for assistance.
Call for Papers - Deadline extension
formal papers - doctoral programme
16th Conference on Intelligent Computer Mathematics
- CICM 2023 -
4���8 September 2023
Emmanuel College, Cambridge, UK (hybrid event)
http://www.cicm-conference.org/2023
----------------------------------------------------------------------
*** Extended deadlines
- Abstract deadline: 3 April 2023 (extended)
- Full paper deadline: 10 April 2023 (extended)
----------------------------------------------------------------------
Digital and computational solutions are becoming the prevalent means
for the generation, communication, processing, storage and curation of
mathematical information.
CICM brings together the many separate communities that have developed
theoretical and practical solutions for mathematical applications such
as computation, deduction, knowledge management, and user interfaces.
It offers a venue for discussing problems and solutions in each of
these areas and their integration.
*** CICM 2023 Invited Speakers ***
- Fr��d��ric Blanqui: Progresses on proof systems interoperability
- Mateja Jamnik: TBA
- Lawrence C. Paulson: Large-Scale Formal Proof for the Working
Mathematician - Lessons learnt from the Alexandria Project
- Martina Seidl: Never trust your solver: Certificates for SAT and QBF
*** CICM 2023 Programme committee ***
- Jes��s Aransay (Universidad de La Rioja, Spain)
- Mauricio Ayala-Rincon (Universidade de Brasil��a, Brazil)
- Haniel Barbosa (Universidade Federal de Minas Gerais, Brazil)
- Jasmin Blanchette (Vrije Universiteit Amsterdam, The Netherlands)
- Kevin Buzzard (Imperial College, UK)
- Isabela Dr��mnesc (West University of Timi��oara, Romania)
- Catherine Dubois (ENSIIE, Evry-Courcouronnes, France) [Co-Chair]
- M��d��lina Era��cu (West University of Timi��oara, Romania)
- William Farmer (McMaster University, Canada)
- John Harrison (Amazon Web Services)
- Tetsuo Ida (University of Tsukuba, Japan)
- Moa Johansson (Chalmers University of Technology, Sweden)
- Fairouz Kamareddine (Heriot-Watt University, UK)
- Daniela Kaufmann (TU Wien, Austria)
- Manfred Kerber (University of Birmingham, UK) [Co-Chair]
- Peter Koepke (University of Bonn, Germany)
- Michael Kohlhase (FAU Erlangen-N��rnberg, Germany)
- Angeliki Koutsoukou-Argyraki (University of Cambridge, UK)
- Temur Kutsia (RISC, Johannes Kepler University Linz, Austria)
- Micaela Mayero (Institut Galil��e, Universit�� Paris Nord, France)
- Bruce R. Miller (NIST, USA)
- Adam Naumowicz (University of Bia��ystok, Poland)
- Claudio Sacerdoti-Cohen (University of Bologna, Italy)
- Sofi��ne Tahar (Concordia University, Canada)
- Olaf Teschke (FIZ Karlsruhe, Germany)
- Josef Urban (Czech Technical University, Czech Republic)
- Stephen M. Watt (University of Waterloo, Canada)
- Freek Wiedijk (Radboud University, The Netherlands)
- Wolfgang Windsteiger (RISC, Johannes Kepler University Linz, Austria)
- Abdou Youssef (The George Washington University, USA)
*** SUBMISSIONS ***
CICM 2023 invites submissions in all topics relating to intelligent
computer mathematics, in particular but not limited to
- theorem proving and computer algebra
- mathematical knowledge management
- digital mathematical libraries
CICM appreciates the varying nature of the relevant research in this
area and invites submissions of different forms.
Formal submissions will be reviewed rigorously and accepted papers
will be published in a formal way:
- regular papers (up to 15 pages including references) present novel
research results
- project and survey papers (up to 15 pages + bibliography) summarize
existing results
- system and dataset descriptions (up to 5 pages including references)
present digital artifacts
- system entry (1 page according to the given LaTeX template) provides
metadata and a quick overview of a new tool or a new release of an
existing tool
Participants of CICM benefit a lot from the exchange with colleagues.
In order to foster this we will provide at the conference an
opportunity to make informal presentations (using posters or laptops)
of work-in-progress, project announcements, position statements, and
system demonstrations. Authors of system and dataset descriptions and
system entries are strongly encouraged to take up this opportunity and
give interested colleagues an in depth impression of their work.
*** Doctoral Programme ***
PhD students are invited to participate in the doctoral programme,
which provides them with a forum to present early results and receive
constructive feedback and mentoring. To attend, submit a two-page
abstract of the thesis describing the research questions, research
plans, completed and remaining research, evaluation plans and
publication plans; a two-page CV that includes background information
(name, university, supervisor), education (degree sought, year/status
of degree, previous degrees), employments, relevant research
experience (publications, presentations, attended conferences or
workshops, etc).
*** Participation / Hybrid Event ***
CICM 2023 will be held as an hybrid event, participation is possible
online or on-site. Authors of accepted papers can choose to present
online or on-site, but at least one author needs to register for the
conference.
*** Important Dates ***
- Abstract deadline: 3 April 2023 (extended)
- Full paper deadline: 10 April 2023 (extended)
- Reviews sent to authors: 9 May 2023 (extended)
- Rebuttals due: 13 May 2023 (extended)
- Notification of acceptance: 20 May 2023 (extended)
- Camera-ready copies due: 12 June 2023 (extended)
- Conference: 4���8 September 2023
Submissions to the doctoral programme
- Submission deadline: 30 June 2023
- Notification of acceptance: 14 July 2023
All submissions should be made via EasyChair at
https://easychair.org/conferences/?conf=cicm2023
CICM 2023 will have proceedings in form of a volume in the Springer
LNAI series, using the LNCS style.
For the LNCS style files, see:
https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…
Hi all,
If you are actively using IP addresses of not-logged-in editors of the
Wikimedia projects for your research or intend to do so in the future,
please read on. Otherwise, you can stop here.
As you know, IP addresses can provide a wealth of information about
not-logged-in editors, including sensitive information such as their
location and organization. This can pose a privacy risk to these editors.
To mitigate this, the Wikimedia Foundation (WMF) is currently working on a
project to mask IP addresses and limit their exposure and storage on our
platform.
The IP masking project can have an impact on your work. Given that the
Research team represents the needs of the Wikimedia research community in
the Wikimedia Foundation, we are reaching out to you to notify you of the
upcoming changes. We do this in coordination with the team responsible for
IP masking.
The change: When WMF launches the IP masking, future edits from
not-logged-in users (sometimes referred to as unregistered users) will no
longer be attributed to their IP addresses. Instead, they will be assigned
auto generated temporary usernames that will be tied to a cookie on their
browsers. As long as the cookie persists, the edits will be attributed to
that user. After a certain period of time (tentatively one year), the
cookie will automatically expire. Users who need access to IP addresses to
protect Wikimedia projects from vandalism or other abuse will be able to do
so on a limited basis and for a limited period of time.
No change. IP addresses of not-logged-in users in the historical data will
remain unchanged. The IP masking rollout will affect future edits (relative
to the time of rollout) only.
Timelines: The projected timeline for early pilot (in 1-2 wikimedia
projects) rollout is between October-December 2023. The team doesn’t yet
have a projected timeline for a complete rollout of this change to all
Wikimedia projects.
What we have considered to offer instead. We understand the importance of
IP addresses for research purposes. To that end:
-
The Research <https://research.wikimedia.org/team.html> and Security
<https://security.wikimedia.org/> teams did an initial exploration of
whether we can offer one or more alternative datasets that can support
existing research that utilizes IP addresses. We concluded that we will not
be able to offer country level data –the most common use-case of IP
addresses to the best of our knowledge – at the revision level at this
point in time.
-
The Research team will consider exploring the option to offer a
user-group level access to researchers who need to have access to this
data. The priority of this work will depend on other priorities of the
Research team as well as an impact assessment based on what we hear from
the researchers who currently work with this data. (See the next paragraph.
)
Impact on your research: If this change creates a significant burden on you
or your research, we want to hear from you by April 30, 2023. You can
communicate this impact by leaving a comment in
https://phabricator.wikimedia.org/T332034. If there is an impact that you
cannot communicate publicly, please write an email to Niharika Kohli <
nkohli(a)wikimedia.org> (IP Masking, Product Manager, also in CC) & myself <
lzia(a)wikimedia.org> (Head of Research). We commit to reviewing all comments
we receive by the deadline, and we commit to exploring ways to support you
to reduce the impact on you and your work. We also ask for your
understanding. If this data is not essential for your work, please consider
using the many other data sources that we make publicly available,
including but not limited to those listed in
https://meta.wikimedia.org/wiki/Research:Data.
Sharing your expertise. If you have conducted research or are aware of
research that the team should take into account as WMF moves forward with
IP masking, please share that with the team on the project’s talk page
<https://meta.wikimedia.org/wiki/Talk:IP_Editing:_Privacy_Enhancement_and_Ab…>
.
Stay updated. You can stay updated about this project through the project’s
dedicated page
<https://meta.wikimedia.org/wiki/IP_Editing:_Privacy_Enhancement_and_Abuse_M…>
.
Please consider this email as a one-time courtesy notification. We may not
send reminders. As a result, if your work may be affected, please take a
note of this email and reach out to us by the deadline. :)
Thanks,
Leila
--
Leila Zia
Head of Research
Wikimedia Foundation
The Wikimedia Foundation has developed a set of ML/AI systems that have
been shaping editing behaviour on Wikipedia. How these tools have
impacted the efficiency and fairness of moderation work will be
discussed in "Balancing Open Participation and Information Quality in
Wikipedia Using Machine Learning", a talk by Benjamin Mako Hill of the
University of Washington. The talk is part of the 2023 Lecture Series of
the Austrian Research Institute for Artificial Intelligence:
https://www.ofai.at/events/lectures2023
Members of the public are cordially invited to attend the talk via Zoom
on Wednesday, 15 February at 18:30 CET (UTC+1):
URL:
https://us06web.zoom.us/j/84282442460?pwd=NHVhQnJXOVdZTWtNcWNRQllaQWFnQT09
Meeting ID: 842 8244 2460
Passcode: 678868
Talk abstract: Peer produced information goods like free/open source
software and Wikipedia are both increasingly important and increasingly
under threat. This talk will describe how Wikipedia has sought to
balance its commitment to open editing and its desire to allow
participation from unvetted and anonymous users with its need to
maintain high information quality in its articles. I will focus on the
way that a set of ML/AI systems developed by the Wikimedia Foundation
allow scholars to measure the value of contributions from anonymous
users and the surprising way that these systems can also be used by the
Wikipedia community to shape editing behavior. I will argue that use of
these ML/AI systems can both improve the efficiency of moderation work
while also making moderation actions more fair to anonymous contributors
who are the source of substantial vandalism by reducing reliance on
social signals and making norm violations by everyone else more visible.
Speaker biography: Benjamin Mako Hill is an Associate Professor in the
University of Washington Department of Communication and an Adjunct
Associate Professor in the Department of Human-Centered Design &
Engineering, the Paul G. Allen School of Computer Science & Engineering,
and the Information School. He is a member of Community Data Science
Collective which he founded with Aaron Shaw. At UW, he is also Affiliate
Faculty in the Center for Statistics and the Social Sciences, the
eScience Institute, and the "Design Use Build" (DUB) group that supports
research on on human computer interaction. He is also a Faculty
Associate at the Berkman Klein Center for Internet and Society at
Harvard University and an affiliate of the Institute for Quantitative
Social Science at Harvard.
--
Dr.-Ing. Tristan Miller, Research Scientist
Austrian Research Institute for Artificial Intelligence (OFAI)
Freyung 6/6, 1010 Vienna, Austria | Tel: +43 1 5336112 12
https://logological.org/ | https://punderstanding.ofai.at/
Hi everyone,
The call for papers for the 10th Wiki Workshop in 2023 is out:
https://wikiworkshop.org/2023/#call Submit your 2-page abstracts by March
23 (all submissions are non-archival). The workshop will take place on May
11, 2023. For more information, see the workshop website [1].
If you have questions about the workshop, please let us know on this list
or at wikiworkshop(a)googlegroups.com.
Looking forward to seeing many of you in this year's edition.
Best,
Pablo Aragón, Wikimedia Foundation
Martin Gerlach, Wikimedia Foundation
Evelin Heidel, Wikimedistas de Uruguay
Emily Lescak, Wikimedia Foundation
Francesca Tripodi, University of North Carolina
Bob West, EPFL
Leila Zia, Wikimedia Foundation
[1] https://wikiworkshop.org/2023/
—
We invite contributions to the 10th edition (!) of Wiki Workshop, which
will take place virtually on May 11, 2023 (tentatively 12:00-19:00 UTC).
Wiki Workshop is the largest Wikimedia research event of the year, aimed at
bringing together researchers who study all aspects of Wikimedia projects
(including, but not limited to, Wikipedia, Wikidata, Wikimedia Commons,
Wikisource, and Wiktionary) as well as Wikimedia developers, affiliate
organizations, and volunteer editors. Co-organized by the Wikimedia
Foundation’s Research team and members of the Wikimedia research community,
the workshop facilitates a direct pathway for exchanging ideas between the
organizations that serve Wikimedia projects and the researchers actively
studying them. New this year: Building on the successful experiences of
organizing Wiki Workshop in 2015 <https://wikiworkshop.org/2015/>, 2016
<https://wikiworkshop.org/2016/>, 2017 <https://wikiworkshop.org/2017/>,
2018 <https://wikiworkshop.org/2018/>, 2019 <https://wikiworkshop.org/2019/>
, 2020 <https://wikiworkshop.org/2020/>, 2021
<https://wikiworkshop.org/2021/>, and 2022 <https://wikiworkshop.org/2022/>
and based on feedback from authors and participants over the years, we are
introducing a few updates to the research track of the workshop for 2023:
-
This 10th edition will take place as a standalone event (rather than in
co-location with a conference, as in previous years).
-
We have changed the format of submissions and will only accept 2-page
extended abstracts (following the successful IC2S2 model).
-
Submissions are non-archival, so we welcome ongoing, completed, and
already published work.
-
We are excited to share that the authors of Wiki Workshop 2023 will have
the opportunity to receive feedback, improve their work, and submit the
extended version of their research paper to a special issue of the ACM
Transactions on the Web, which will have a dedicated open call for papers
later in 2023.
Topics include, but are not limited to:
-
new technologies and initiatives to grow content, quality, equity,
diversity, and participation across Wikimedia projects
-
use of bots, algorithms, and crowdsourcing strategies to curate, source,
or verify content and structured data
-
bias in content and gaps of knowledge on Wikimedia projects
-
relation between Wikimedia projects and the broader (open) knowledge
ecosystem
-
exploration of what constitutes a source and how/if the incorporation of
other kinds of sources are possible (e.g., oral histories, video)
-
detection of low-quality, promotional, or fake content (misinformation
or disinformation), as well as fake accounts (e.g., sock puppets)
-
questions related to community health (e.g., sentiment analysis,
harassment detection, tools that could increase harmony)
-
motivations, engagement models, incentives, and needs of editors,
readers, and/or developers of Wikimedia projects
-
innovative uses of Wikipedia and other Wikimedia projects for AI and NLP
applications and vice versa
-
consensus-finding and conflict resolution on editorial issues
-
dynamics of content reuse across projects and the impact of policies and
community norms on reuse privacy, security, and trust
-
collaborative content creation
-
innovative uses of Wikimedia projects' content and consumption patterns
as sensors for real-world events, culture, etc.
-
open-source research code, datasets, and tools to support research on
Wikimedia contents and communities
-
connections between Wikimedia projects and the Semantic Web
-
strategies for how to incorporate Wikimedia projects into media literacy
interventions
This year’s Wiki Workshop solicits extended abstracts (PDF format, maximum
2 pages, including references). Submissions that exceed the 2-page limit
will be automatically rejected. Authors may include 1 additional page with
figures and/or tables (including captions) only. Initial submissions
require names and affiliations of authors, 5 keywords, a title, abstract,
and a main text outlining the contribution, methods, findings, and impact
of the work, whichever is relevant. Submissions will be non-archival and as
a result may have already been published, under review, or ongoing
research. All submissions will be reviewed by multiple members of the Wiki
Workshop Program Committee. The names of the authors will be revealed to
the reviewers, whereas reviewers will remain anonymous to authors. Authors
of accepted abstracts will be invited to present their research in a
pre-recorded oral presentation with dedicated time for live Q&A on May 11,
2023. Accepted abstracts may be shared on the website prior to the event.
The template for formatting the submission as well as the submission link
to easychair will be made available by February 23.
--
Martin Gerlach (he/him) | Senior Research Scientist | Wikimedia Foundation