PoliticalNLP 2022 : First Workshop on Natural Language Processing for Political sciences Co-located with LREC 2022

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First Call for Papers
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First Workshop on Natural Language Processing for Political sciences Co-located with LREC 2022, Marseille, France
Website: https://sites.google.com/view/politicalnlp2022/home
Conference Website: https://lrec2022.lrec-conf.org/en/
Submission deadline: April 8, 2022
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*Description*

Applications using large volumes of structured and unstructured text data are becoming common in social and political sciences research. As a result, text processing methods used to predict, learn, and discover new insights from socio-political text data that is large in volume and variety, have seen enormous growth in recent years.

This workshop will explore the multifarious aspects of effective Natural Language Processing techniques for socio-political data. The workshop aims to provide a research platform dedicated to new methods and techniques on text processing of socio-political content and exploring the use of such methods on information extraction and analysis. The workshop will solicit original research contributions related to the theme, which may include (but is not limited to):
Migration flows, disaster or disease prediction, and forecasting
Modeling global events or human activities based on text analysis
Identification and geo-location of social media content
Social-based web platform for disaster management
Resource allocation using social media
Monitoring emergency responses among social crowds
Analyzing the diffusion of emergent information
Exploiting text generation for crisis response and rescue activities
Ethical concerns and ethical design of NLP applications in socio-political sciences

The PoliticalNLP workshop will provide a venue for discussing the implementation of language technologies in the social and political sciences domain. Computational Social and Political scientists will be invited to report and discuss their NLP 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 these domains.

Contributions can be short or long papers. Short paper submission must describe original and unpublished work without exceeding four (4) pages plus any number of pages for references. Short papers include a small, focused contribution; work in progress; a negative result; an opinion piece; an interesting application nugget. Long paper submissions must describe substantial, original, completed, and unpublished work without exceeding eight (8) pages plus any number of pages for references.

*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 2022 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.

*Important Dates*

Submission deadline (short and long papers): April 8, 2022
Notification to authors: May 2, 2022
Submission of camera-ready abstracts/papers: May 23, 2022
Early registration deadline: May 31, 2022
Workshop: June 24, 2022 (morning session)

*Organizers*

Haithem Afli, ADAPT Centre, Munster Technological University, Ireland
Mehwish Alam, FIZ Karlsruhe - Leibniz Institute for Information Infrastructure, Germany
Cristina Blasi Casagran, Universidad Autónoma de Barcelona, Spain
Houda Bouamor, Carnegie Mellon University, Qatar
Sahar Ghannay, Université Paris-Saclay, CNRS, LISN, France