K-MIN

About the workshop

Newsrooms handle information with various sources and formats. Processing this heterogeneous information and making sense out of it is key to news production and dissemination steps. With the proliferation of Large Language Models, there is renewed interest and scope in applying knowledge representations to effectively handle and utilize such diverse information. The synergy between LLMs and knowledge graphs, for example, offer potential to build knowledge representations from textual data in a retrieval-friendly way, while minimising hallucinations or factually-incorrect responses. Integrating such techniques in the newsroom workflow, however, remains challenging. Discussions about AI in journalism often focus on the automated generation of news reports to various capacities, whereas its application to knowledge, the most fundamental tool in a newsroom, is often overlooked.

In this exciting backdrop of emerging solutions, the first edition of the workshop on “Knowledge Management in Newsrooms”, in conjunction with the 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW-24), Amsterdam, presents a platform for researchers and practitioners working with the knowledge representations in the domain of journalism.

Programme

Conference date: 26.11.2024

Time: 13:30

Venue: Room No: L017, Centrum Wiskunde and Informatica, Science Park 123, 1098 XG Amsterdam.

Details

  • 13:30 - 13:55 An Exploration of LLM-Guided Detection of Discursive Patterns in Dutch Social Media (Swarupa Hardikar, Maya Sappelli and Annette Klarenbeek)
  • 13:55 - 14:20 Online News Classification Using Large Language Models with Semantic Enrichment (Joana Santos, Nuno Silva, Carlos Ferreira and João Gama)
  • 14:20 - 14:45 Opportunities and Challenges of Using AI News Anchors from the Perspectives of Indian Journalists (Bhavesh Chhipa and Dr. Prabhat Dixit)
  • 14:45 - 15:10 Take (no) chances: How stochasticity and prompt formulation affect the accuracy of LLMs for fact-checking (Victoria Vziatysheva, Mykola Makhortykh and Maryna Sydorova)

The workshop proceedings will be included in the CEUR joint proceedings for Workshops, Tutorials, Posters and Demos of EKAW 2024. We welcome submissions in short/long form, in PDF format, in alignment with the CEUR-WS template published in the CEUR-WS guidelines.

Organizers

Dr. Reshmi Gopalakrishna Pillai
Vrije University Amsterdam
r.pillai(at)vu(dot)nl
https://www.linkedin.com/in/reshmi-g-pillai/

Reshmi is a PostDoc Researcher at the Department of Communication Science in the Vrije University Amsterdam, in the consortium project ‘Towards Responsible AI for Local Journalism’. She focuses on the adoption and implementation of artificial intelligence techniques, specifically natural language processing, in the context of local journalism. Her current research explores the construction of structured knowledge bases in the context of regional news media organizations in the Netherlands. Previously (2019-2023), she was a Lecturer at the Informatics Institute, University of Amsterdam, in the Master's program in Information Studies (Data Science track). She holds a PhD (December 2021) from the University of Wolverhampton for her thesis on the expressions of psychological stress in tweets.

Dr. Laurence Dierickx
University of Bergen / Université Libre de Bruxelles
laurence.dierickx(at)uib(dot)no / laurence.dierickx(at)ulb(dot)be
https://ohmybox.info

Laurence Dierickx is a postdoctoral researcher at the Department of Information Science and Media Studies at the University of Bergen and a fellow researcher at the Digital Democracy Centre at the University of Southern Denmark. Her research focuses on AI and generative AI in fact-checking, ranging from integration into professional practices to risk mitigation strategies. She also teaches digital and data journalism at the Brussels School of Journalism (ULB). She holds a Master's degree in Sciences and Technologies of Information and Communication and a PhD from the Université Libre de Bruxelles, where her thesis explored automated news production through a socio-technical lens. Her interdisciplinary approach advances the understanding of AI-driven journalism and its ethical implications through ethics, data-centric approaches and human-computer interactions.

Program committee

Dr. Hannes Cools, University of Amsterdam

Prof. Dr. Antske Fokkens, Vrije University Amsterdam

Dr. Marc Gallofré Ocaña, University of Bergen

Dr. Leo Leppänen, University of Helsinki

Prof. Dr. Carl-Gustav Lindén, University of Bergen

Dr. Silvia Majo Vazquez, Vrije University of Amsterdam

Nicolas Mattis, Vrije University of Amsterdam

Dr. Subhayan Mukerjee, National University Singapore

Dr. Valeria Resendez, Vrije University of Amsterdam

Dr. Nadja Shaetz, University of Hamburg

Stefanie Sirén-Heikel, University of Helsinki

Prof. Dr. Wouter van Atteveldt, Vrije University Amsterdam

Prof. Dr. Arjen van Dalen, University of Southern Denmark