The use of large amounts of structured and unstructured text data in social and political sciences research has become increasingly prevalent. Consequently, there has been a significant growth in the development of text processing methods aimed at predicting, learning, and uncovering new insights from socio-political text data that is extensive and diverse.

This workshop will delve into the various aspects of effective Natural Language Processing techniques for socio-political data. Its objective is to establish a research platform dedicated to exploring novel methods and techniques for processing socio-political content and investigating their application in information extraction and analysis.

Launched in 2022 in conjunction with the LREC 2022 conference, this workshop continues to evolve as a platform for fostering collaborative research and exploration. 

This year’s workshop will focus on the theme “Opportunities and Challenges of Generative AI and LLMs in Social and Political Sciences Research.” However, contributions on any topic related to the theme are welcome, including but not limited to:

  •   Migration flows, disaster or disease prediction, and forecasting
  •   Modelling 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
  •   Analysing 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 aims to provide a platform for discussing the implementation of language technologies in the field of social and political sciences. Computational social and political scientists will be invited to present and discuss their NLP tools, comparing them to traditional coding approaches. Computational linguistics and machine learning practitioners and researchers will benefit from engaging with real-world use cases in these domains.

Contributions to the workshop can take the form of:

–        Regular long papers – up to eight (8) pages maximum, presenting substantial, original, completed, and unpublished work.

–        Short papers – up to four (4) pages, describing a small focused contribution, negative results, system demonstrations, etc.

–        Position papers – up to eight (8) pages, discussing key hot topics, challenges and open issues, as well as cross-fertilization between NLP, Social Science, and other disciplines.

(*) Excluding any number of additional pages for references, ethical consideration, conflict-of-interest, as well as data and code availability statements.

In line with the WiNLP initiative, we recognize and address the demographic imbalance within computational linguistics. To champion diversity and inclusivity, we actively encourage submissions from under-represented groups. Embracing diverse perspectives enriches our discourse and strengthens our collective pursuit of knowledge in this field.

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-COLING 2024 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 & Paper Submission Instructions

LREC-COLING 2024 asks for full papers from 4 pages to 8 pages (plus more pages for references and appendices, if needed), which must strictly follow the LREC stylesheet ( Author’s Kit ) which is available on the conference website.

Contributions can be short or long papers. Characteristics of 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.

Reviewing will be double-blind, so the papers should not reveal the authors’ identities. Accepted papers will be published in the workshop proceedings.

Double submission policy: Parallel submission to other meetings or publications is possible but must be immediately notified to the workshop organizers.

For further information, please contact Haithem Afli (haithem.afli(at)adaptcentre(dot)ie)

Workshop Organizers                                       

General Chair: Haithem Afli, ADAPT Centre, Munster Technological University, Ireland

Program Chairs: 

  • Houda Bouamor, Carnegie Mellon University, Qatar
  • Sahar Ghannay, Université Paris-Saclay, CNRS, LISN, France
  • Cristina Blasi Casagran, Autonomous University of Barcelona, Spain

Program Committee

  • Cristina Blasi Casagran, Universidad Autónoma de Barcelona, Spain
  • Yiyi Chen, FIZ Karlsruhe – Leibniz Institute for Information Infrastructure, Germany
  • Adam Zebrowski, Microsoft, Saudi Arabia
  • Bruno Andrade, Munster Technological University, Ireland
  • Lenka Dražanová, European University Institute, Italy
  • Georgios Stavropoulos, The Centre for Research and Technology, Greece
  • Mohammed Hasanuzzaman, Munster Technological University, Ireland
  • Amira Barhoumi, LIUM, Le Mans Université, France
  • Patrick Paroubek, Université Paris-Saclay, CNRS, LISN, France
  • Colleen Boland, Universidad Autónoma de Barcelona, Spain
  • Andrea Iana, University of Mannheim, Germany
  • Nikolaos Gkevrekis, CERTH, Greece
  • Praveen Joshi, Munster Technological University, Ireland
  • Patrick Paroubek, Université Paris-Saclay, CNRS, LISN, France
  • Ilias Iliopoulos, CERTH, Greece
  • Zsolt Kardkovacs, Munster Technological University, Ireland
  • Pintu Lohar, Dublin City University, Ireland
  • Suman Adhya, Indian Association for the Cultivation of Science, India
  • Valentin Barriere, Joint Research Center, Italy

More information here

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