Dear all,
due to several requests we decided to extend the deadlines for the
industry track.
The new dates are as follows:
Paper Submission Deadline: June 7, 2022 (11:59 pm, Hawaii time
- originally May 30)
Notification of Acceptance: June 13, 2022 (11:59 pm, Hawaii time)
Camera-Ready Presentation: August 15, 2022 (11:59 pm, Hawaii time)
To address the needs and interests of industry SEMANTICS invites
enterprise solutions that deal with semantic processing of data and/or
information in areas like Linked Data, Data Publishing, Semantic Search,
Recommendation Services, Sentiment Detection, Search Engine Add-Ons,
Thesaurus and/or Ontology Management, Text Mining, Data Mining, and any
related fields. All submissions have a strong focus on real world
applications beyond the prototypical status and demonstrate the power of
semantic systems!
For details please go to: https://2022-eu.semantics.cc/cfp
Looking forward to your submissions! Stay tuned and stay safe!
With kind regards,
Florian Bauer, Marco Brattinga & Christian Dirschl
-- Industry Track Chairs --
Hi everyone!
I have a question concerning the relevance search on wikipedia articles, and Robert West from EPFL pointed me to this mailing list as the best chance to answer it. I have been checking the elasticsearch query performed by the wikipedia api when it runs a basic search on the articles. More precisely, I am talking of the following api call:
https://en.wikipedia.org/w/api.php?action=query&list=search&format=json&srl…
The actual elasticsearch query is available with the cirrusDumpQuery parameter:
https://en.wikipedia.org/w/api.php?action=query&list=search&format=json&srl…
There are many things going on in that query, but my question is related with the rescoring of the results that gives the final score. In particular, with the clause
{
"sltr": {
"model": "enwiki-20220421-20180215-query_explorer",
"params": {
"query_string": "architecture mathematics"
}
}
}
I understand that the results are passed together with the keywords to a stored machine learning model whose name is enwiki-20220421-20180215-query_explorer. This, as far as I understand, is done using the LTR plugin for elasticsearch (https://github.com/o19s/elasticsearch-learning-to-rank). My question is the following: Is this model openly available anywhere? If so, could you point me where? If not, do you know why is it not openly available and yet used by Wikipedia?
I posted this as part of a question on stackoverflow some days ago. Please check https://stackoverflow.com/questions/72213203/elasticsearch-query-for-wikipe… for more context and some more related questions.
I thank you all in advance, have a nice day!
Aitor Pérez
Machine Learning Engineer
EPFL Graph - CEDE - EPFL
aitor.perez(a)epfl.ch
The Third Wikidata Workshop
Call for Papers
Co-located with the 21st International Conference on Semantic Web (ISWC
2022).
Date: October 23 or 24, 2022
The workshop will be held online, afternoon European time.
Website: https://wikidataworkshop.github.io/2022/
== Important dates ==
Papers due: *Friday, *29 July 2022
Notification of accepted papers: Friday, September 23, 2022
Camera-ready papers due: Monday, October 3, 2022
Workshop date: October 23/24, 2022
== 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 primarily 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 are less
interested in are works that 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.
This year, we also added a track for already published work. To foster
conversations around the topic of Wikidata, we invite authors of papers
published at other conferences to submit their papers to present at the
workshop. These will not be included in the proceedings but gives a chance
for authors to interact with the community.
We welcome interdisciplinary work, as well as interesting applications that
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 oral
presentations. For this reason, all accepted papers will be presented in
short talks and accompanied by a poster. All works will be presented
online.
== 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
- Abstract Wikipedia
== Submission guidelines ==
We welcome the following types of contributions.
= Track 1: Novel Works =
The papers in this track will be peer-reviewed by at least three
researchers. Accepted papers will be published as open access papers on
CEUR (authors can also waive this). We invite the following types of papers:
- 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 resources 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.
Papers have to be submitted through easychair (Please add “[NOVEL]” in the
beginning of the title on the submission page so we know that you are
submitting to this track):
https://easychair.org/my/conference?conf=wikidataworkshop2022
= Track 2: Published works =
This track welcomes papers previously published at a peer-reviewed research
venue, to be presented and discussed in the workshop. They do not have to
follow the formatting and page limit instructions from Track 1, and can
instead be submitted in the original format.
Previously published papers will be reviewed by the organising committee in
terms of topical fit and prominence of the publication venue. They will not
be published as part of the proceedings. We invite the following types of
papers:
- Full research paper: Previously published research contributions
- Resource paper: Previously published datasets or other resources that are
important or interesting to the community
- Demo paper: Presenting a previously published system critically enabled
by Wikidata
Papers have to be submitted through easychair (please add “[PUBLISHED]” in
the beginning of the title on the submission page so we know that you are
submitting to this track):
https://easychair.org/my/conference?conf=wikidataworkshop2022
== Proceedings ==
The complete set of papers from the Novel Works Track will be published
with the CEUR Workshop Proceedings (CEUR-WS.org).
== Organizing committee ==
Lucie-Aimée Kaffee, University of Copenhagen, lucie.kaffee[[(a)]]gmail.com
Simon Razniewski, Max Planck Institute for Informatics, srazniew[[@]]
mpi-inf.mpg.de
Kholoud Alghamdi, King's College London, kholoud.alghamdi[[(a)]]kcl.ac.uk
Gabriel Maia Rocha Amaral, King's College London, gabriel.amaral[[@]]
kcl.ac.uk
== Programme committee ==
Seyed Amir Hosseini Beghaeiraveri, Heriot-Watt University
Houcemeddine Turki, Data Engineering and Semantics Research Unit,
University of Sfax, Tunisia
Filip Ilievski, Information Sciences Institute, University of Southern
California, Marina del Rey, CA, USA
Mahir Morshed, University of Illinois at Urbana-Champaign
Daniel Garijo, Universidad Politécnica de Madrdid
Niel Chah, University of Toronto & Microsoft
Alasdair Gray, Heriot Watt University
Thomas Pellissier Tanon, Lexistems
John Samuel, CPE Lyon
Dennis Diefenbach, The QA Company
Heiko Paulheim, University of Mannheim
Cristina Sarasua, University of Zurich
Pavlos Vougiouklis, Huawei
Pierre-Henri Paris, Télécom Paris
Lydia Pintscher, Wikimedia Deutschland
Isaac Johnson, Wikimedia Foundation
Alessandro Piscopo, BCC
Luis Galárraga, Inria
Danai Symeonidou, INRAE
Andrew D. Gordon, Microsoft Research and University of Edinburgh
David Abián, King’s College London
Elisavet Koutsiana, King’s College London
--
Lucie-Aimée Kaffee
++++ apologies for cross-postings ++++
* A satellite event of the Conference on Complex Systems 2022<https://www.ccs2022.org/index.php>
* Date of Event: October 19-20, 2022 (half-day session)
* Submissions Deadline: June 19, 2022
* Venue: Palma De Mallorca, Spain (and virtual)
* Previous event: MIMODE2021<https://www.demogr.mpg.de/en/news_events_6123/news_press_releases_4630/news…>
* Contact: mimode2022(a)easychair.org<mailto:mimode2022@easychair.org>
The recent availability of massive amounts of digital data have profoundly revolutionized research on migration and mobility, enabling scientists to quantitatively study individual and collective mobility patterns at different granularities as generated by human activities in their daily life. Harnessing such digital data offers many new opportunities to study migration and mobility and fill in the gaps left by traditional data. At the same time, such innovative data sources also come with several limitations, biases, and challenges, which have led to diverging research methodologies and frameworks, requiring even greater effort in their operationalization and communication to stakeholders and policy makers.
The aim of this satellite session is to bring together researchers from different fields and practitioners from around the world to facilitate a conversation on the use of innovative digital data sources, new methodologies, empirical findings, and critical challenges of studying migration and mobility in the digital era.
Topics of interest include, but are not limited to:
1. New data sources for mobility and migration research, challenges and opportunities
2. Internal and international migration, short- and long-term mobility
3. Modeling and predicting human mobility patterns
4. Machine learning and AI methods for studying mobility
5. Longitudinal analyses and empirical studies of mobility and migration
6. Socio-economic and environmental drivers of migration
7. Integration and segregation of migrant populations
8. Measuring the impact of natural disasters, conflicts, climate change, and the COVID-19 pandemic on migration
9. Access to mobility data, open science, and privacy concerns
10. Evaluation and development of migration policy
Call for Abstracts
We welcome submissions of abstracts on ongoing or published work that fit the topics of the event. The submissions must be a single PDF-file of maximum 2 pages in English including the title, list of authors and affiliations, abstract text, descriptive figure or table, and references (optional). The abstracts can be in any format or style as long as they do not exceed the page and word limits. Alternatively, authors can use an abstract template (click here<https://docs.google.com/document/d/1odthFs5v8a4-PIveHQE_L_5ImBFuHivD/edit?u…> to view our optional formatting template).
Abstracts must be submitted electronically by June 19, 2022, through the Easychair platform at the following link: https://easychair.org/conferences/?conf=mimode2022
All submissions will be evaluated by the Program Committee on the basis of quality and fit to the satellite theme.
Oral presentations will be allocated about 12 minutes, followed by 5 minutes of Q&A. Please note that the presenting author must register to the main conference as announced on CCS2022<https://www.ccs2022.org/index.php> website.
Important Dates
June 19, 2022 - Deadline for abstract submissions (midnight CEST)
July 11, 2022 - Notification of abstract acceptance for oral presentation
July 25, 2022 - Deadline for early bird registration
October 19-20, 2022 - MIMODE 2022 satellite (half-day session)
Registration & Venue
MIMODE 2022 is a satellite of the Conference on Complex Systems CCS2022<https://www.ccs2022.org/index.php>, and will take place in Palma de Mallorca, Spain (and online) on October 19-20, 2022.
Satellite participants (with or without abstract submission) will have to register following the procedure described in the CCS2022 conference website: https://www.ccs2022.org/index.php/registration/registration-fees
Presenting authors can indicate their availability to travel to Spain in October 2022 in the submission platform. We will consider researchers' needs and organize our satellite event accordingly as we approach the date of the event. More details will follow soon.
The conference venue will be the Auditorium of Palma de Mallorca Convention Center located in: Paseo Marítimo 18, 07014, Palma de Mallorca, Illes Balears (Spain).
To know more about the venue, please visit the conference website: https://www.ccs2022.org/index.php/general-information/venue
Program
TBA
Invited speakers
TBA
Program Committee
TBA
Organizers
Jisu Kim, Research Scientist, Laboratory of Digital and Computational Demography, MPIDR.
Jisu holds a PhD in Data Science from Scuola Normale Superiore in Italy. She has worked on exploring and establishing novel methods to improve relevant statistics of international migration using social media data. Her research focuses on the intersection of migration sciences, economics of migration, complex social networks, statistical models and data-driven algorithms.
Daniela Perrotta, Research Scientist, Laboratory of Digital and Computational Demography, MPIDR.
Daniela Perrotta completed her PhD in Complex Systems for Life Sciences at the University of Turin with a fellowship at the Laboratory of Digital and Computational Epidemiology at the ISI Foundation in Italy. Her research focuses on harnessing innovative data-collection schemes and computational methods for modeling human mobility and disease spread.
Contact the Organizers
mimode2022(a)easychair.org<mailto:mimode2022@easychair.org>
--
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+++ Apologies for cross-postings +++
The Max Planck Institute for Demographic Research (MPIDR) is inviting applications from qualified and highly motivated students for a PhD student position in the Lab of Digital and Computational Demography<http://demogr.mpg.de/en/laboratories/digital_and_computational_demography_5…>.
The MPIDR is one of the leading demographic centers in the world. It is part of the Max Planck Society, a network of more than 80 institutes that form Germany’s premier basic-research organization. Max Planck Institutes have an established record of world-class research and they offer a unique environment that combines the best aspects of an academic setting and a research laboratory.
The Lab of Digital and Computational Demography, headed by MPIDR Director Emilio Zagheni, is looking for candidates with strong quantitative and programming skills and with research interests in human mobility, health, and disease ecology.
Short Description of the PhD Project
Human mobility is a key process in health and disease ecology, shaping the mixing patterns that facilitate the spread of both pathogens and vectors. The successful candidate is expected to contribute and advance a project that uses novel techniques to study human mobility and its implications for disease dynamics and inequality. Particular attention would be devoted to links between mobility and mosquito-borne diseases, including the analysis of multiple sources of mobility data and mosquito surveillance as a way to better inform models of mosquito risk and epidemiological patterns.
Supervisory Team
This project will be supervised by an interdisciplinary team of renowned scholars that includes Daniela Perrotta (MPIDR), Emilio Zagheni (MPIDR), John Palmer (Universitat Pompeu Fabra - UPF), and Frederic Bartumeus (Centre d'Estudis Avançats de Blanes – CEAB-CSIC). The PhD student is expected to be in residence at the MPIDR and enrolled in the PhD program of the Faculty of Political and Social Sciences at UPF. Additionally, the PhD student will receive support for research visits at UPF and CEAB-CSIC, in order to complete mandatory coursework and to have further scientific exchange with the research team in Barcelona.
For questions and additional information regarding the PhD project, please contact Daniela Perrotta (perrotta(a)demogr.mpg.de<mailto:perrotta@demogr.mpg.de?subject=Application%20%2F%20Inquiry%20PhD%20Student%20Position>).
The PhD studentship offers an excellent opportunity for motivated students to work with a highly international team of researchers, to take advantage of the interdisciplinary intellectual environment at the MPIDR, as well as substantial support for travel, research training and data acquisition.
The admitted student is expected to be part of the International Max Planck Research School for Population, Health and Data Science (IMPRS-PHDS) that merges demography, epidemiology and data science. IMPRS-PHDS equips doctoral students not only with advanced knowledge of the theory and methods of demography and epidemiology (broadly defined as ‘population health’), but also with strong technical skills in statistics, mathematical modeling, and computational and data management methods (broadly referred to as ‘data science’). PHDS supports strong interdisciplinary research training and exchange within a network of universities in Europe and the US. The research school offers a core training program in Rostock, extensive networking opportunities across partner sites, and high-quality supervision across at least two institutes. For more information on the IMPRS-PHDS curriculum please see www.imprs-phds.mpg.de<https://www.imprs-phds.mpg.de/>.
How to Apply
Applications must be submitted online via this portal<https://survey.demogr.mpg.de/index.php/633483?lang=en> by June 17, 2022 and include as a single pdf file, in English:
Curriculum Vitae, including a list of your scholarly publications.
1. A motivational statement (maximum two pages) explaining why you applied, how your research interests fit with the project; how the MPIDR could foster your career development; and describing your technical skills and areas of expertise.
2. Copies of transcripts of undergraduate and master’s degrees. Applicants should hold a master’s degree or equivalent at the time of starting the PhD.
3. Names and contact information for 2 academic referees.
4. One writing sample.
The starting date is flexible, but no later than November 1, 2022. The PhD student is offered a 3-year contract with remuneration based on the salary structure of the German public sector (Öffentlicher Dienst, TVöD Bund) currently starting at 34,295.22 € gross a year. Online interviews will be held on July 11-12, 2022.
The MPIDR is an equal opportunities employer. Our work atmosphere includes respectful treatment of each other, with gender, nationality, religion, disability, age, cultural origin, and sexual identity playing no role. We aim to have an institutional culture that enables everyone to develop their individual skills and competencies.
The Max Planck Society offers a broad range of measures to support the reconciliation of work and family. These are complemented by the MPIDR’s own initiatives. The Society has been awarded the certificate “Work and Family” which is granted to institutions committed to establishing a family-friendly corporate culture by binding target agreements. The MPIDR collaborates with a network of local day-care centers that provides childcare places for the children of Institute staff. The Max Planck Society has contracts with a private family service company that offers services such as arranging child care on short notice in various cities in Germany for parents who attend conferences, care services for children of school age up to 14 years, and support for those caring for family members and relatives. The MPIDR also practices flexible working-time models, which include at least one home office day per week, and scheduling meetings only within core working hours. To help accompanying spouses and partners find appropriate work at their new location, the MPIDR works in close cooperation with Dual-Career Partners in regional networks.
Our Institute values diversity and is keen to employ individuals from minorities.
The Max Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals. Furthermore, the Max Planck Society seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply.
--
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*** Apologies for cross postings ***
[Abstract Submission Deadline Extended to May 23, 2022
Update Information on hybrid format]
Call for Papers
formal papers - informal papers - doctoral programme
15th Conference on Intelligent Computer Mathematics
- CICM 2022 -
September 19-23, 2022
Tbilisi, Georgia (hybrid event)
http://www.cicm-conference.org/2022
----------------------------------------------------------------------
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 2022 Invited Speakers:
* Erika Abraham (RWTH Aachen University)
* Deyan Ginev (FAU Erlangen-N��rnberg and NIST)
* S��bastien Gou��zel (IRMAR, Universit�� de Rennes 1)
CICM 2022 Programme committee:
see https://www.cicm-conference.org/2022/cicm.php?event=&menu=pc
CICM 2022 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:
1) Formal submissions will be reviewed rigorously and accepted papers
will be published in a volume of Springer LNAI:
* 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 existent tool
2) Informal submissions will be reviewed with a positive bias and
selected for presentation based on their relevance for the
community.
* informal papers may present work-in-progress, project
announcements, position statements, etc.
* posters and system demos will be presented in parallel in special
sessions
3) The doctoral programme provides PhD students with a forum to
present early results and receive constructive feedback and
mentoring.
*** Participation / Hybrid Event ***
CICM 2022 wil 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: May 23 (extended)
- Full paper deadline: May 27 (extended)
- Reviews sent to authors: June 19
- Rebuttals due: June 23
- Notification of acceptance: July 4
- Camera-ready copies due: July 18
- Conference: September 19-23, 2022
Informal submissions and doctoral programme
- Submission deadline: July 15
- Notification of acceptance: July 29
All submissions should be made via EasyChair at
https://easychair.org/conferences/?conf=cicm2022
As in previous years, the CICM 2022 proceedings will be published in
the LNAI subseries of Springer LNCS.
For the LNCS style files, see:
https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…
Hello everyone,
The next Research Showcase, *Gaps and Biases in Wikipedia*, will be
live-streamed Wednesday, May 18, at 9:30 AM PST/16:30 UTC. View your local
time here <https://zonestamp.toolforge.org/1652891400>.
YouTube stream: https://www.youtube.com/watch?v=Q8FlunZ0mH4
You are welcome to ask questions via YouTube chat or on IRC at
#wikimedia-research.
This month's presentations:
Ms. Categorized: Gender, notability, and inequality on Wikipedia
By Francesca Tripodi (University of North Carolina at Chapel Hill)
For the last five decades, sociologists have argued that gender is one of
the most pervasive and insidious forms of inequality. Research demonstrates
how these inequalities persist on Wikipedia - arguably the largest
encyclopedic reference in existence. Roughly eighty percent of Wikipedia's
editors are men and pages about women and women's interests are
underrepresented. English language Wikipedia contains more than 1.5 million
biographies about notable writers, inventors, and academics, but less than
nineteen percent of these biographies are about women. To try and improve
these statistics, activists host “edit-a-thons” to increase the visibility
of notable women. While this strategy helps create several biographies
previously inexistent, it fails to address a more inconspicuous form of
gender exclusion. Drawing on ethnographic observations, interviews, and
quantitative analysis of web-scraped metadata this talk demonstrates that
women’s biographies are more frequently considered non-notable and
nominated for deletion compared to men’s biographies. This disproportionate
rate is another dimension of gender inequality on Wikipedia previously
unexplored by social scientists and provides broader insights into how
women’s achievements are (under)valued in society.
Controlled Analyses of Social Biases in Wikipedia Bios
By Yulia Tsvetkov (University of Washington)
Social biases on Wikipedia could greatly influence public opinion.
Wikipedia is also a popular source of training data for NLP models, and
subtle biases in Wikipedia narratives are liable to be amplified in
downstream NLP models. In this talk I'll present two approaches to
unveiling social biases in how people are described on Wikipedia, across
demographic attributes and across languages. First, I'll present a
methodology that isolates dimensions of interest (e.g., gender), from other
attributes (e.g., occupation). This methodology allows us to quantify
systemic differences in coverage of different genders and races, while
controlling for confounding factors. Next, I'll show an NLP case study that
uses this methodology in combination with people-centric sentiment analysis
to identify disparities in Wikipedia bios of members of the LGBTQIA+
community across three languages: English, Russian, and Spanish. Our
results surface cultural differences in narratives and signs of social
biases. Practically, these methods can be used to automatically identify
Wikipedia articles for further manual analysis—articles that might contain
content gaps or an imbalanced representation of particular social groups.
You can also watch our past research showcases here:
https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
Emily, on behalf of the Research team
--
Emily Lescak (she / her)
Senior Research Community Officer
The Wikimedia Foundation
Dear all,
due to several requests we decided to extend the deadlines for the R&I
track.
The new dates are as follows:
Abstract Submission Deadline: May 16, 2022 (11:59 pm, Hawaii
time - originally May 9 – non-mandatory)
Paper Submission Deadline: May 23, 2022 (11:59 pm, Hawaii time
- originally May 16)
Notification of Acceptance: June 20, 2022 (11:59 pm, Hawaii time)
Camera-Ready Paper: July 04, 2022 (11:59 pm, Hawaii time)
SEMANTiCS 2022 especially invites contributions that target the
intersections between computational semantics and neighboring research
areas such as machine learning, language technologies, sensor
technologies, distributed ledgers and beyond.
For details please go to: https://2022-eu.semantics.cc/cfp
Looking forward to your submissions! Stay tuned and stay safe!
With kind regards,
Anastasia Dimou & Sebastian Neumaier
-- R&I Track Chairs --
Hi all,
Really exciting new special issue on semantic media that may be of interest
to Wikipedia/Wikidata researchers. See below and let me know if you have
any questions! Abstract deadline is July 15.
All best,
Heather (and Andrew)
*---------------------------*
*Dr Heather Ford*
Associate Professor and Head of Discipline, Digital and Social Media
<https://protect-au.mimecast.com/s/FQHeCWLV8zfVZBE1c6Xxp0?domain=uts.edu.au>
School of Communication
<https://protect-au.mimecast.com/s/LanMCXLWMAfWjYQlUVwgoH?domain=uts.edu.au>
, University of Technology, Sydney
<https://protect-au.mimecast.com/s/TW2LCYW8MBSwmx7KS9GWuj?domain=uts.edu.au/>
(UTS)
Affiliate: UTS Data Science Institute
<https://protect-au.mimecast.com/s/IVXUCZY1WDc0AN61hyw6D9?domain=uts.edu.au>
| Associate: UTS Centre for Media Transition
<https://protect-au.mimecast.com/s/rkiJC1WL9zSlxY4rHYfasg?domain=uts.edu.au>
| Associate Member: UTS Centre for Research on Education in a Digital
Society
<https://protect-au.mimecast.com/s/DnQsC2xM9AUgWwYLUMyBYW?domain=uts.edu.au>
w: hblog.org
<https://protect-au.mimecast.com/s/BxKxC3QN90SOoQkjSYqg7J?domain=hblog.org/>
/ t: @hfordsa
<https://protect-au.mimecast.com/s/U-uPC4QO9DSqE1VZUNo71T?domain=twitter.com> /
pronouns: she/her
*University of Technology Sydney*
Faculty of Arts and Social Sciences
PO Box 123. Broadway NSW 2007 Australia
I acknowledge the Gadigal People of the Eora Nation and the Boorooberongal
People of the Dharug Nation upon whose ancestral lands our campuses now
stand. I pay respect to Elders past, present and emerging, acknowledging
them as the traditional custodians of knowledge for these lands.
*Call for Papers*
*Social Media + Society** Special Issue: Semantic Media*
*Editors: Andrew Iliadis and Heather Ford*
This special issue focuses on “semantic media,” which we define as media
technologies that primarily orchestrate and convey facts, answers,
meanings, and “knowledge” about things directly in media products, rather
than lead people to other sources. Search engines and virtual assistants
respond directly to questions based on textual or verbal searches (e.g.,
“Things to do in Philadelphia?” or “What is the capital of Israel?”). The
special issue is thus dedicated to the often-invisible ways (to the
non-specialist) that internet companies are now actively involved in
constructing “knowledge” about the world. Organizations like Apple, Google,
Microsoft, Facebook, and Amazon extract, curate, and store facts served to
users in new and emerging media products. Such processes have significant
implications for the politics of knowledge sharing in the future.
We seek papers that examine how design decisions “bake” these facts into
the apps and platforms people use daily while focusing on the
infrastructures dedicated to orchestrating and presenting this information.
The goal is to understand the technologies that will drive social and
political outcomes when large internet companies become a primary conduit
through which people directly acquire an understanding of facts about the
world. We also seek to understand how governments, nonprofit, and
nongovernmental organizations engage these media technologies. Semantic
media are less about searching for keywords and matches on different
websites that are then ranked for people to choose. Instead, they deal with
identifying and describing entities (things like people, products, and
places) and directing interactions with those entities (actions like
purchasing, scheduling, and contacting). How do semantic media identify
concepts and connect related information about them? How do companies and
organizations produce facts and organize the data? From where does the data
originate? What do these semantic processes mean for web users and
administrators? What types of gatekeeping or safety checks do companies and
organizations perform concerning these facts?
Today’s semantic media have a long history reaching back to the “Semantic
Web” project initiated by web inventor Tim Berners-Lee. Yet, media
researchers do not adequately cover how companies and organizations
implement semantic technologies on platforms relative to their central
role. These semantic technologies are in proprietary and open source
products, and extensive media platforms are now using them to provide facts
and represent knowledge to various publics. Google’s Knowledge Graph is a
database of facts that Google uses to provide quick answers to the public,
and such graphs are in use at other companies. At the same time, Wikipedia
has a product called Wikidata that similarly stores facts about the world
in data formats through which various apps can retrieve the data.
Researchers and journalists also use semantic technologies for search
engine optimization, fact-checking practices, and data sharing and
organization. This special issue thus focuses on such platformized versions
of fact production and examines the underlying infrastructures, histories,
and modeling techniques used in knowledge representation systems.
We are interested in quantitative, qualitative, and critical approaches and
papers that propose new methods, theories, and frameworks.
*Areas of interest:*
• The creation or transmission of facts, answers, meanings,
definitions, and “knowledge” across media systems and their platforms
• Answers from virtual assistants such as Alexa, Siri, Cortana,
Bixby, etc.
• Answers from search engines such as Google, Bing, Baidu,
Yandex, etc.
• Products like knowledge panels, infoboxes, carousels, rich
results, maps, etc.
• Open-source semantic technologies such as Schema.org, Wikidata,
etc.
• Proprietary semantic technologies such as Google’s Knowledge
Graph, etc.
• Fact-checking practices for misinformation and disinformation
across semantic media platforms
• Search engine optimization and semantic search practices
• Semantic infrastructure projects such as the semantic web,
linked data, etc.
• Semantic governance organizations such as the World Wide Web
Consortium, etc.
• Semantic technologies such as metadata, markup languages,
knowledge bases, knowledge graphs, web schemas, applied ontologies, and
enterprise semantic software
• Semantic, linguistic, and conceptual theories involving rules
and logic, theories of meaning, ontology, taxonomy, ideas of truth, social
ontology, etc.
*Timeline:*
• Extended 1000-word abstracts due Fri July 15
• Decisions out to authors Fri Aug 19
• Full 8000-word manuscript due Fri Nov 18
• Final decisions January 2023
• Submit to journal February 2023
• Publication spring 2023
*Send submissions to andrew.iliadis(a)temple.edu
<andrew.iliadis(a)temple.edu> and heather.ford(a)uts.edu.au
<heather.ford(a)uts.edu.au> with the subject header “Social Media + Society
Special Issue: Semantic Media”*
*Link: *https://journals.sagepub.com/page/sms/collections/cfp
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Hello everyone,
We at CopeNLU and the Digital Democracies Institute are currently running
an online survey on the potential harms and misuses of Natural Language
Processing technologies and research. We, therefore, ask researchers in the
field of natural language processing to fill the following survey to give
us an insight into their concerms.
We would really appreciate it if you could take a few minutes to fill out
the survey.
The survey takes about 20 minutes to complete and is available here:
copenlu.limesurvey.net/987789
Thank you!
Lucie-Aimée Kaffee, Arnav Arora, Zeerak Talat
--
Lucie-Aimée Kaffee