++ CALL FOR PAPERS ++  

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Seventh International Workshop on Narrative Extraction from Texts (Text2Story'24)  

Held in conjunction with the 46th European Conference on Information Retrieval (ECIR'24)  

March 24th, 2024 – Glasgow, Scotland 

Website: https://text2story24.inesctec.pt 

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++ Important Dates ++  

    - Submission Deadline: January 10th, 2024  

    - Acceptance Notification: February 23rd, 2024 

    - Camera-ready copies: March 15th, 2024 

    - Workshop: March 24th, 2024 

++ Overview ++   

Over these past years, significant breakthroughs, led by Transformers and Large Language Models (LLMs), have been made in understanding natural language text. However, the ability to capture, represent, and analyze contextual nuances in longer texts is still an elusive goal, let alone the understanding of consistent fine-grained narrative structures in text. In the seventh edition of the Text2Story workshop, we aim to bring to the forefront the challenges involved in understanding the structure of narratives and in incorporating their representation in well-established frameworks, as well as in modern architectures (e.g., transformers) and AI-powered language models (e.g, chatGPT) which are now common and form the backbone of almost every IR and NLP application. It is hoped that the workshop will provide a common forum to consolidate the multi-disciplinary efforts and foster discussions to identify the wide-ranging issues related to the narrative extraction task.  

++ List of Topics ++  

Research works submitted to the workshop should foster the scientific advance on all aspects of storyline generation and understanding from texts including but not limited to narrative information extraction aspects, narratives representation, knowledge extraction, ethics and bias in narratives, datasets and evaluation protocols and narrative applications such as visualization of narratives, multi-modal aspects, Q&A, etc. To this regard, we encourage the submission of high-quality and original submissions covering the following topics:  

Information Extraction Aspects 

• Temporal Relation Identification 

• Temporal Reasoning and Ordering of Events 

• Causal Relation Extraction and Arrangement 

• Big Data Applied to Narrative Extraction 

Narrative Representation 

• Annotation protocols 

• Narrative Representation Models 

• Lexical, Syntactic, and Semantic Ambiguity in Narrative Representation 

Narrative Analysis and Generation 

• Argumentation Analysis 

• Language Models and Transfer Learning in Narrative Analysis  

• Narrative Analysis in Low-resource Languages 

• Multilinguality: Multilingual and Cross-lingual Narrative Analysis 

• Comprehension of Generated Narratives 

• Story Evolution and Shift Detection 

• Automatic Timeline Generation 

Datasets and Evaluation Protocol 

• Evaluation Methodologies for Narrative Extraction 

• Annotated datasets 

• Narrative Resources 

Ethics and Bias in Narratives 

• Bias Detection and Removal in Generated Stories 

• Ethical and Fair Narrative Generation 

• Misinformation and Fact Checking 

Narrative Applications 

• Narrative-focused Search in Text Collections 

• Narrative Summarization 

• Narrative Q&A 

• Multi-modal Narrative Summarization 

• Sentiment and Opinion Detection in Narratives 

• Social Media Narratives 

• Narrative Simplification 

• Personalization and Recommendation of Narratives 

• Storyline Visualization 

++ Dataset ++  

We challenge the interested researchers to consider submitting a paper that makes use of the tls-covid19 dataset - published at ECIR'21 - under the scope and purposes of the text2story workshop. tls-covid19 consists of a number of curated topics related to the Covid-19 outbreak, with associated news articles from Portuguese and English news outlets and their respective reference timelines as gold-standard. While it was designed to support timeline summarization research tasks it can also be used for other tasks (e.g., Q&A), especially when combined with Large Language Models (LLMs) like ChatGPT.  A script to reconstruct and expand the dataset is available at https://github.com/LIAAD/tls-covid19. The article itself is available at this link: https://link.springer.com/chapter/10.1007/978-3-030-72113-8_33  

++ Submission Guidelines ++   

We solicit the following types of contributions: 

• Full papers 

 up to 8 pages + references 

    Original and high-quality unpublished contributions to the theory and practical aspects of the narrative extraction task. Full papers should introduce existing approaches, describe the methodology and the experiments conducted in detail. Negative result papers to highlight tested hypotheses that did not get the expected outcome are also welcomed. 

• Short papers 

up to 5 pages + references 

    Unpublished short papers describing work in progress; position papers introducing a new point of view, a research vision or a reasoned opinion on the workshop topics; and dissemination papers describing project ideas, ongoing research lines, case studies or summarized versions of previously published papers in high-quality conferences/journals that is worthwhile sharing with the Text2Story community, but where novelty is not a fundamental issue. 

• Demos | Resource Papers 

up to 5 pages + references 

    Unpublished papers presenting research/industrial demos; papers describing important resources (datasets or software packages) to the text2story community; 

       Submissions will be peer-reviewed by at least two members of the programme committee. The accepted papers will appear in the proceedings published at CEUR workshop proceedings (indexed in Scopus and DBLP) as long as they don't conflict with previous publication rights. 

++ Workshop Format ++  

   Participants of accepted papers will be given 15 minutes for oral presentations.  

++ Invited Speakers ++ 

   Jochen L. Leidner, Coburg University of Applied Sciences, Germany 

   Mirella Lapata, University of Edinburgh, Scotland 

++ Organizing committee ++  

   Ricardo Campos (INESC TEC; University of Beira Interior, Covilhã, Portugal) 

   Alípio M. Jorge (INESC TEC; University of Porto, Portugal) 

   Adam Jatowt (University of Innsbruck, Austria) 

   Sumit Bhatia (Media and Data Science Research Lab, Adobe) 

   Marina Litvak (Shamoon Academic College of Engineering, Israel) 

++ Proceedings Chair ++ 

    João Paulo Cordeiro (INESC TEC & Universidade da Beira do Interior) 

    Conceição Rocha (INESC TEC)  

++ Web and Dissemination Chair ++  

    Hugo Sousa (INESC TEC & University of Porto)   

    Behrooz Mansouri (Rochester Institute of Technology)  

++ Program Committee ++  

Álvaro Figueira (INESC TEC & University of Porto)  

Andreas Spitz (University of Konstanz)  

Antoine Doucet (Université de La Rochelle)  

António Horta Branco (University of Lisbon)  

Anubhav Jangra (IIT Patna, Japan)  

Arian Pasquali (Faktion AI)  

Bart Gajderowicz (University of Toronto)  

Begoña Altuna (Universidad del País Vasco)  

Behrooz Mansouri (Rochester Institute of Technology)  

Brenda Santana (Federal University of Rio Grande do Sul)  

Bruno Martins (IST & INESC-ID, University of Lisbon)  

Brucce dos Santos (Computational Intelligence Laboratory (LABIC) - ICMC/USP)  

David Semedo (Universidade NOVA de Lisboa) 

Deya Banisakher (Florida International University)  

Dhruv Gupta (Norwegian University of Science and Technology)  

Evelin Amorim (INESC TEC)  

Henrique Lopes Cardoso (LIACC & University of Porto)  

Ignatius Ezeani (Lancaster University)  

Irina Rabaev (Shamoon College of Engineering)  

Ismail Altingovde (Middle East Technical University)  

João Paulo Cordeiro (INESC TEC & University of Beira Interior)  

Liana Ermakova (HCTI, Université de Bretagne Occidentale)  

Luca Cagliero (Politecnico di Torino)  

Ludovic Moncla (INSA Lyon)  

Luis Filipe Cunha (INESC TEC & University of Minho)  

Marc Finlayson (Florida International University)  

Marc Spaniol (Université de Caen Normandie)  

Mariana Caravanti (Computational Intelligence Laboratory (LABIC) - ICMC/USP)  

Moreno La Quatra (Kore University of Enna)  

Natalia Vanetik (Sami Shamoon College of Engineering)  

Nuno Guimarães (INESC TEC & University of Porto)  

Pablo Gervás (Universidad Complutense de Madrid)  

Paulo Quaresma (Universidade de Évora)  

Purificação Silvano (CLUP & University of Porto)  

Ross Purves (University of Zurich)  

Satya Almasian (Heidelberg University)  

Sérgio Nunes (INESC TEC & University of Porto)  

Sriharsh Bhyravajjula (University of Washington)  

Udo Kruschwitz (University of Regensburg)  

Valentina Bartalesi (ISTI-CNR, Italy) 

++ Contacts ++  

Website: https://text2story24.inesctec.pt  

For general inquiries regarding the workshop, reach the organizers at: text2story2024@easychair.org