[Air-L] CFP: Automated Extraction of Socio-political Events from News (AESPEN) @ LREC 2020

[ali hürriyetoglu]

Apologies for cross-posting

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Call for papers:  Automated Extraction of Socio-political Events from News
(AESPEN) @ LREC 2020

URL: https://emw.ku.edu.tr/aespen-2020/

Submission deadline: February 22nd, 2020

Submission page: https://www.softconf.com/lrec2020/AESPEN2020/

Workshop date: May 12th, 2020

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Call for Papers

Automatic construction of event databases has long been a challenge for the
natural language processing (NLP) community in terms of algorithmic
approaches and language resources. At the same time, social and political
scientists have been working on creating socio-political event databases
for their studies for decades. The need for collecting data for
socio-political science studies has been satisfied by manual,
semi-automatic, and automatic approaches. However, the results yielded by
these approaches to date are either not of sufficient quality or require
tremendous effort to be replicated on new data. On the one hand, manual or
semi-automatic methods require high-quality human effort; on the other
hand, state-of-the-art event detection systems are not accurate to the
point that their output may be directly usable, without human moderation.
Finally, the NLP community has not achieved a consensus on the treatment of
events both in terms of task definition and appropriate techniques for
their detection.

Given the aforementioned limitations, there is an increasing tendency to
rely on machine learning (ML) and NLP methods to deal better with the vast
amount and variety of data to be collected. This workshop aims to inspire
the emergence of innovative technological and scientific solutions in the
field of event detection and event metadata extraction from news, as well
as the development of evaluation metrics for event recognition. Moreover,
time the workshop will aim at triggering a deeper understanding of the
usability of socio-political event datasets.

References:

Lorenzini, J., Makarov, P., Kriesi, H., & Wueest, B. (2016). Towards a
Dataset of Automatically Coded Protest Events from English-language
Newswire Documents. In Paper presented at the Amsterdam Text Analysis
Conference URL: http://bruno-wueest.ch/assets/files/Lorenzini_etal_2016.pdf

Wang, W., Kennedy, R., Lazer, D., & Ramakrishnan, N. (2016). Growing pains
for global monitoring of societal events. Science, 353(6307), 1502-1503.
URL: http://science.sciencemag.org/content/353/6307/1502
Motivation and Topics of Interest

Automating political event collection requires the availability of
gold-standard corpora that can be used for system development and
evaluation. Moreover, automated tool performances need to be reproducible
and comparable. Although a tremendous effort is being spent on creating
socio-political event databases such as ACLED, GDELT, MMAD, and ICEWS,
there has not been much progress in harmonization across event schemas and
tasks. This limitation causes the definition of the events and automated
event information collection tool performances to be restricted to single
projects. Consequently, the lack of comparable and reproducible settings
hinders progress on this task.

We invite contributions from researchers in NLP, ML and AI involved in
automated event data collection, as well as researchers in Social and
Political Sciences, Conflict Analysis and Peace studies, who make use of
this kind of data for their analytical work. Our goal is to enable the
emergence of innovative NLP/IE solutions that can help to deal with the
current stream of information, manage the risks of information overload,
identify different sources and perspectives, and provide unitary and
intelligible representations of the larger and long-term storylines behind
news articles.

Our workshop will provide a venue for discussing the creation and
facilitation of language resources in the social and political sciences
domain. Social and political scientists will be interested in reporting and
discussing their desiderata from automated tools in comparison to their
traditional coding approaches. Computational linguistics and machine
learning practitioners and researchers will benefit from being challenged
by real-world use cases, in terms of event data extraction, representation
and aggregation.

We invite work on all aspects of automated coding of socio-political events
from mono- or multi-lingual news sources. This includes (but is not limited
to) the following topics:

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   Event metadata extraction
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   Source Bias mitigation
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   Event Data Schema and representation
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   Event information duplication detection
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   Extracting events beyond a sentence in a document
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   Training Data collection/annotation processes
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   Event coreference (in- and cross-document)
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   Sub-event and event subset relations
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   Event dataset evaluation and validity metrics
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   Event datasets quality assessments
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   Defining, populating and facilitating event ontologies
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   Automated Tools for relevant tasks
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   Understanding the limits that are introduced by copyright rules
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   Ethical concerns and ethical design

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:

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   a small, focused contribution;
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   work in progress;
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   a negative result;
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   a position paper.

Proceedings should be submitted on the START system, in compliance with the
style sheet adopted for the LREC Proceedings (to be found here:
https://lrec2020.lrec-conf.org/en/submission2020/authors-kit/)

Papers should be submitted in PDF form through the AESPEN submission site:
https://www.softconf.com/lrec2020/AESPEN2020/ .

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.

Workshop Proceedings will be published on the LREC 2020 website.
Identify, Describe, and Share your LRs!

Describing your LRs in the LRE Map is now a normal practice in the
submission procedure of LREC (introduced in 2010 and adopted by other
conferences). To continue the efforts initiated at LREC 2014 about “Sharing
LRs” (data, tools, web-services, etc.), authors will have the possibility,
when submitting a paper, to upload LRs in a special LREC repository. This
effort of sharing LRs, linked to the LRE Map for their description, may
become a new “regular” feature for conferences in our field, thus
contributing to creating a common repository where everyone can deposit and
share data.

As scientific work requires accurate citations of referenced work so as to
allow the community to understand the whole context and also replicate the
experiments conducted by other researchers, LREC 2020 endorses the need to
uniquely Identify LRs through the use of the International Standard
Language Resource Number (ISLRN, www.islrn.org), a Persistent Unique
Identifier to be assigned to each Language Resource. The assignment of
ISLRNs to LRs cited in LREC papers will be offered at submission time.
Shared Task

We will organize a shared-task that will provide a setting that consists of
data, task definition, and evaluation schema. Participants of this
shared-task will have the possibility to report their results in the
workshop after peer-review of their working notes. A session will be
dedicated to discuss the results of the shared task during the workshop.
Keynote Speaker

The keynote speech will be delivered by Prof. Clionadh Raleigh.

Title: Too soon? The limitations of AI for event data

Bio:

Prof. Clionadh Raleigh is a professor of Political Geography focused on
modern disorder and political elite networks in developing states. She is
the director of the ACLED project which produces and analyzes real-time
data on political violence and protest in the world’s most unstable states.
Moreover, she is recipient of two European Research Council Grants.
Important dates

All dates are in 2020 and (23:59 GMT+1)

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   January 14th: Announcing the shared task
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   February 14th: Cut-off date for the shared task results
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   February 22nd: Workshop paper submission deadline
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   March 1st: Submission deadline for the working notes of the shared task
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   March 13th: Notification of acceptance
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   April 2nd: Camera-ready deadline
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   May 12th, 2020: The workshop date

Contact

Do not hesitate to contact ahurriyetoglu at ku.edu.tr or
vanni.zavarella at ec.europa.eu for any questions or comments.
Organizing Committee

Ali Hürriyetoğlu (Koc University)

Hristo Tanev (European Commission – Joint Research Center)

Erdem Yörük (Koc University and University of Oxford)

Vanni Zavarella (European Commission – Joint Research Center)
Programme Committee

Svetla Boycheva (Institute of Information and Communication Technologies,
Bulgarian Academy of Sciences)

Fırat Durusan (Koc University)

Theresa Gessler (University of Zürich)

Christian Göbel (University of Vienna)

Burak Gürel (Koc University)

Bernardo Magnini (Fondazione Bruno Kessler (FBK))

Osman Mutlu (Koc University)

Arzucan Özgür (Boğaziçi University)

Jakub Piskorski (Polish Academy of Sciences)

Lidia Pivovarova (University of Helsinki)

Benjamin J. Radford (UNC Charlotte)

Clionadh Raleigh (University of Sussex)

Parang Saraf (Virginia Tech)

Philip Schrodt (Parus Analytical Systems)

Manuela Speranza (Fondazione Bruno Kessler, Trento)

Çağrı Yoltar (Koc University)

Aline Villavicencio (The University of Sheffield)

Kalliopi Zervanou (Eindhoven University of Technology)