[Air-L] First Call for Papers and Shared Task Participation: CASE @ ACL-IJCNLP 2021 Automated Extraction of Socio-political Events from Text

[ali hürriyetoglu]

Apologies for cross-posting

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Call for Papers and Shared Task Participation: Challenges and Applications
of Automated Extraction of Socio-political Events from Text (CASE) @ ACL-
IJCNLP 2021

URL: https://emw.ku.edu.tr/case-2021/

April 26, 2021: Submission deadline

May 28, 2021: Notification of Acceptance

June 7, 2021: Camera-ready papers due

Workshop dates: August 5-6, 2021

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Today, the unprecedented quantity of easily accessible data on social,
political, and economic processes offers ground-breaking potential in
guiding data-driven analysis in social and human sciences and in driving
informed policy-making processes. The need for precise and high-quality
information about a wide variety of events ranging from political violence,
environmental catastrophes, and conflict, to international economic and
health crises has rapidly escalated (Porta and Diani, 2015; Coleman et al.
2014). Governments, multilateral organizations, local and global NGOs, and
social movements present an increasing demand for this data to prevent or
resolve conflicts, provide relief for those that are afflicted, or improve
the lives of and protect citizens in a variety of ways. For instance, Black
Lives Matter protests and conflict in Syria events are only two examples
where we must understand, analyze, and improve the real-life situations
using such data.

Event extraction has long been a challenge for the natural language
processing (NLP) community as it requires sophisticated methods in defining
event ontologies, creating language resources, and developing algorithmic
approaches (Pustojevsky et al. 2003; Boroş, 2018; Chen et al. 2021). Social
and political scientists have been working to create socio-political event
databases such as ACLED, EMBERS, GDELT, ICEWS, MMAD, PHOENIX, POLDEM,
SPEED, TERRIER, and UCDP following similar steps for decades. These
projects and the new ones increasingly rely on machine learning (ML) and
NLP methods to deal better with the vast amount and variety of data in this
domain (Hürriyetoğlu et al. 2020). Automation offers scholars not only the
opportunity to improve existing practices, but also to vastly expand the
scope of data that can be collected and studied, thus potentially opening
up new research frontiers within the field of socio-political events, such
as political violence & social movements. But automated approaches as well
suffer from major issues like bias, generalizability, class imbalance,
training data limitations, and ethical issues that have the potential to
affect the results and their use drastically (Lau and Baldwin 2020; Bhatia
et al. 2020; Chang et al. 2019). Moreover, the results of the automated
systems for socio-political event information collection may not be
comparable to each other or not of sufficient quality (Wang et al. 2016;
Schrodt 2020).

Socio-political events are varied and nuanced. Both the political context
and the local language used may affect whether and how they are reported.
Therefore, all steps of information collection (event definition, language
resources, and manual or algorithmic steps) may need to be constantly
updated, leading to a series of challenging questions: Do events related to
minority groups are represented well? Are new types of events covered? Are
the event definitions and their operationalization comparable across
systems? (Hürriyetoğlu 2019, 2020a, 2020b) This workshop aims to seek
answers to this kind of questions, to inspire innovative technological and
scientific solutions for tackling the aforementioned issues, and to
quantify the quality of the automated event extraction systems. Moreover,
the workshop will trigger a deeper understanding of the performance of the
computational tools used and the usability of the resulting socio-political
event datasets.

We invite contributions from researchers in computer science, NLP, ML, AI,
socio-political sciences, conflict analysis and forecasting, peace studies,
as well as computational social science scholars involved in the collection
and utilization of socio-political event data. This includes (but is not
limited to) the following topics
        * Extracting events in and beyond a sentence
        * Training data collection and annotation processes
        * Event coreference detection
        * Event-event relations, e.g., subevents, main events, causal
relations
        * Event dataset evaluation in light of reliability and validity
metrics
        * Defining, populating, and facilitating event schemas and
ontologies
        * Automated tools and pipelines for event collection related tasks
        * Lexical, Syntactic, and pragmatic aspects of event information
manifestation
        * Development and analysis of rule-based, ML, hybrid, and
human-in-the-loop approaches for creating event datasets
        * COVID-19 related socio-political events
        * Applications of event databases
        * Online social movements
        * Bias and fairness of the sources and event datasets
        * Estimating what is missing in event datasets using internal and
external information
        * Novel event detection
        * Release of new event datasets
        * Ethics, misinformation, privacy, and fairness concerns pertaining
to event datasets
        * Copyright issues on event dataset creation, dissemination, and
sharing
        * Qualities of the event information on various online and offline
platforms
*** Keynotes ***

We invite leading scholars in computational linguistics and social and
political sciences to deliver keynote speeches on collecting and exploiting
socio-political event information.

*Computational linguistics*: Elizabeth Boschee is the Director of the
Boston office of the University of Southern California’s Information
Sciences Institute and a Senior Supervising Computer Scientist in the
Emerging Activities division. Her current efforts focus on cross-lingual
information extraction, retrieval, and summarization, specifically
targeting low or zero-resource settings, e.g. cross-lingual settings with
<1M words of bitext or event extraction from non-English languages with
only English training data. Prior to joining ISI, Boschee spent 17 years at
BBN Technologies. As a Lead Scientist there, she was the chief architect of
the BBN ACCENT event coder, the technology behind the W-ICEWS event data,
which more than doubled the precision (while still increasing recall) of
the previously deployed solution for CAMEO event coding.

*Social and political sciences*: Kristine Eck is an Associate Professor at
the Department of Peace and Conflict Research at Uppsala University, where
she serves as the Director of the Uppsala Rotary Peace Center. Her research
interests concern coercion and resistance, including human rights, police
misconduct, state surveillance, and conflict data production. She served as
the Director of the Uppsala Conflict Data Program (UCDP) 2017-2018 and has
been a Visiting Researcher at Oxford University, Copenhagen University, the
University of Notre Dame, and Kobe University. Dr. Eck’s research has been
funded by the Swedish Research Council, the Swedish Foundation for
Humanities and Social Sciences, and the Norwegian Foreign Ministry.
**** Submissions *****

This call solicits full papers reporting original and unpublished research
on the topics listed above. The papers should emphasize obtained results
rather than intended work and should indicate clearly the state of
completion of the reported results. Submissions should be between 4 and 8
pages in total. Authors are also invited to submit short papers not
exceeding 4 pages (plus two additional pages for references). Short papers
should describe:

   - a small, focused contribution;
   - work in progress;
   - a negative result;
   - a position paper.
   - a report on shared task participation.

Papers should be submitted on the START page of the workshop (link: TBD) in
PDF format, in compliance with the ACL-IJCNLP 2021 author guidelines
provided on https://2021.aclweb.org/calls/papers.

The reviewing process will be double-blind and papers should not include
the authors’ names and affiliations. Each submission will be reviewed by at
least three members of the program committee. If you do include any author
names on the title page, your submission will be automatically rejected. In
the body of your submission, you should eliminate all direct references to
your own previous work. Finally, the workshop Proceedings will be published
on ACL Anthology.
**** Shared tasks ****

We are preparing a cross-lingual (Spanish, Portuguese, and English), which
was only in English in previous events we organized, a socio-political
event information classification and extraction task. Moreover, we are
preparing two additional data challenges about protests pertaining to
BlackLivesMatter and COVID19[3] <https://emw.ku.edu.tr/case-2021/#_ftn3>.
These challenges will be about automatically replicating the spatiotemporal
distribution of a manually curated events list. Common Crawl News will be
exploited as a data source. Moreover, a Twitter dataset will be shared with
the participants as well.

A Codalab page will be set up for each task. Participating teams will be
required to submit a report, which will be peer-reviewed, describing the
methods and results they ran on the data. We encourage submissions of the
system papers on our available benchmarks (ProtestNews @ CLEF 2020
<https://clef2020.clef-initiative.eu/> and AESPEN @ LREC 2020
<https://lrec2020.lrec-conf.org/en/>). Please find details of these
datasets and shared tasks on Hürriyetoğlu et al. (2019, 2020a, and 2020b).

Please send an e-mail to ahurriyetoglu at ku.edu.tr if you would like to
participate in any of the shared tasks.
**** Important dates ****

April 26, 2021: Workshop Paper Due Date

May 28, 2021: Notification of Acceptance

June 7, 2021: Camera-ready papers due

August 5-6, 2021: Workshop Dates

Note: All deadlines are 11:59PM UTC-12:00 ("anywhere on Earth").


**** Organization Committee ****

Ali Hürriyetoğlu (Koc University, Turkey)

Hristo Tanev (Joint Research Centre (JRC), European Commission, Italy)

Vanni Zavarella (Joint Research Centre (JRC) of the European
Commission, Italy)

Reyyan Yeniterzi (Sabancı University, Turkey)

Aline Villavicencio (University of Sheffield, the United Kingdom; and
Institute of Informatics, Federal University of Rio Grande do Sul, Brazil)

Erdem Yörük (Koc University, Turkey),

Deniz Yuret (Koc University, Turkey),

Jakub Piskorski  (Polish Academy  of Sciences, Poland),

Gautam Kishore Shahi (University of Duisburg-Essen, Germany).


**** Program Committee ****

Tommaso Caselli (University of Groningen, the Netherlands),

Osman Mutlu (Koc University, Turkey),

Fırat Duruşan (Koc University, Turkey),

Ali Safaya (Koc University, Turkey),

Bharathi Raja Asoka Chakravarthi (Insight SFI Centre for Data Analytics,
the United Kingdom),

Gautam Kishore Shahi (University of Duisburg-Essen, Germany),

Jakub Piskorski (Polish Academy of Sciences, Poland),

Matina Halkia (European Commission – Joint Research Centre, Italy),

Benjamin J. Radford (UNC Charlotte, the United States),

Mark Lee (University of Birmingham, the United Kingdom),

YiJyun Lin (University of Nevada, the United States),

Fredrik Olsson (RISE, Sweden),

Kristine Eck (Uppsala University, Sweden),

Nelleke Oostdijk (Radboud University, the Netherlands),

Francielle Vargas (University of São Paulo, Brazil),

Farhana Liza (University of Essex, the UK),

Nicoletta Calzolari (Institute for Computational Linguistics, Italy),

Milena Slavcheva (Bulgarian Academy of Sciences, Bulgaria),

Harish Tayyar Madabushi (University of Birmingham, the United Kingdom),

Ritesh Kumar (Dr. Bhimrao Ambedkar University, India),

Alexandra DeLucia (Johns Hopkins University, United States),

Jasmine Lorenzini (University of Geneva, Switzerland),

Kalliopi Zervanou Eindhoven (University of Technology the Netherlands).