• Designing for Automated Sports Commentary Systems 

  Andrews, Peter Daniel; Nordberg, Oda Elise; Borch, Njål; Guribye, Frode; Fjeld, Morten (Chapter, 2024)

  Advancements in Natural Language Processing (NLP) and Computer Vision (CV) are revolutionizing how we experience sports broadcasting. Traditionally, sports commentary has played a crucial role in enhancing viewer understanding ...

• FootyVision: Multi-Object Tracking, Localisation, and Augmentation of Players and Ball in Football Video 

  Andrews, Peter Daniel; Borch, Njål; Fjeld, Morten (Chapter, 2024)

  Football video content analysis is a rapidly evolving field aiming to enrich the viewing experience of football matches. Current research often focuses on specific tasks like player and/or ball detection, tracking, and ...

• Transparency and fact-checking in open societies 

  Dierickx, Laurence; Linden, Carl-Gustav (Journal article; Peer reviewed, 2024)

  Transparency is more than a motto for professional fact-checkers; it is a professional requirement that permeates their daily practice. Although transparency has been theorised and critiqued extensively in journalism ...

• Exploring the Ethical Challenges of AI and Recommender Systems in the Democratic Public Sphere 

  Seddik, Khadiga Mahmoud Abdalla (Journal article; Peer reviewed, 2024)

  The rapid integration of Artificial Intelligence (AI) and Recommender Systems (RSs) into digital platforms has brought both opportunities and ethical concerns. These systems, designed to personalize content and optimize ...

• Evaluating GraphRAG’s Role in Improving Contextual Understanding of News in Newsrooms. 

  Mosolygo, Balazs Jozsef; Fatemi, Bahareh; Rabbi, Fazle; Opdahl, Andreas Lothe (Journal article; Peer reviewed, 2024)

  In a newsroom, journalists are frequently tasked with reporting on complex events, such as conflicts, where understanding the broader context and nuanced details is crucial for accurate and insightful reporting. The challenge ...

• How do Norwegian enterprises create awareness of cyber security? 

  Mykkeltvedt, Ivar; Opdahl, Andreas Lothe (Journal article; Peer reviewed, 2024)

  The increasing digitisation of society means that Norwegian enterprises experience daily cyberattacks. Most successful attacks today are due to human error, and cybersecurity awareness has never been more important. We ...

• Can Large Language Models Support Editors Pick Related News Articles? 

  Mahmood, Bilal; Elahi, Mehdi; Steskal, Lubos; Touileb, Samia (Journal article; Peer reviewed, 2024)

  Editors and journalists play an important role on news platforms. Besides creating trustworthy news stories, they also provide valuable expertise on which stories are placed on the front page and hand-pick related articles ...

• Revolutions: an introduction to the #AoIR2023 special issue 

  Lokot, Tetyana; Demirkol Tönnesen, Naciye Özlem; Rodriguez-Amat, Joan Ramon (Journal article; Peer reviewed, 2024)

  This paper introduces the ‘Revolutions’ themed special issue which includes research presented at the 24th annual Association of Internet Researchers (AoIR) conference (2023). The conference theme centered on revolutions, ...

• Screens as Battlefields: Fact‐Checkers’ Multidimensional Challenges in Debunking Russian‐Ukrainian War Propaganda 

  Dierickx, Laurence; Linden, Carl-Gustav (Journal article; Peer reviewed, 2024)

  This study examines the challenges fact-checkers face when dealing with war propaganda and how their socio-professional contexts influence these obstacles. Using a mixed-methods approach, the research identifies common ...

• Topic-Based Communication Between Agents 

  Galimullin, Rustam; Velázquez-Quesada, Fernando R. (Journal article; Peer reviewed, 2024)

  Communication within groups of agents has been lately the focus of research in dynamic epistemic logic. This paper studies a recently introduced form of partial (more precisely, topic-based) communication. This type of ...

• A review on deep learning methods for heart sound signal analysis 

  Partovi, Elaheh; Babic, Ankica; Gharehbaghi, Arash (Journal article; Peer reviewed, 2024)

  Introduction: Application of Deep Learning (DL) methods is being increasingly appreciated by researchers from the biomedical engineering domain in which heart sound analysis is an important topic of study. Diversity in ...

• CLIPping the Deception: Adapting Vision-Language Models for Universal Deepfake Detection 

  Khan, Sohail Ahmed; Dang Nguyen, Duc Tien (Chapter, 2024)

  The recent advancements in Generative Adversarial Networks (GANs) and the emergence of Diffusion models have significantly streamlined the production of highly realistic and widely accessible synthetic content. As a result, ...

• Skriften på veggen: Selvmordstematikken i NRKs ungdomsserie Rådebank 

  Lysne, Anders (Journal article; Peer reviewed, 2024)

  This article analyzes the theme of suicide in NRK's successful youth drama Rod Knock (Rådebank). Departing from a genre perspective on youth drama conventions within Norwegian and Nordic public service broadcasting drama, ...

• Clinical Validation of M-TONX: A Novel Combo Rebound Tonometer and Pachymeter 

  Nilforushan, Naveed; Yousefi, Mozafar; Babic, Ankica; Gharehbaghi, Arash (Journal article; Peer reviewed, 2024)

  Purpose: This study aims to perform a clinical investigation of an innovative rebound technology-based device, the M-TONX, to simultaneously measure intraocular pressure (IOP) and central corneal thickness (CCT). Methods: ...

• Cascading Power 

  Ågotnes, Thomas; Christoff, Zoe (Journal article; Peer reviewed, 2024)

  Cascading phenomena in social networks happen when the adoption of some behaviour by initial adopters causes some of their immediate friends to adopt which again causes some of their friends’ friends to adopt, and so on. ...

• Rawr: Kitchen, rage, Judith and I 

  Ceuterick, Maud Eurydice (Journal article; Peer reviewed, 2024)

  Through aggressive repetitions and superimpositions of sound and images, this video (essay) proposes to give an audiovisual form to Judith Butler’s theorisation of gender as a performance made of repetitions of stylised ...

• Philosophical Perspectives on Recommender Systems: Ethical Implications, Biases, and Their Impact on Autonomy and Privacy 

  Klimashevskaia, Anastasiia (Journal article; Peer reviewed, 2024)

  Recommender Systems (RSs) assist users in navigating overwhelming amounts of digital information by offering personalized suggestions. While invaluable, these systems raise concerns about biases, fairness, as well as user ...

• Advancing Visual Food Attractiveness Predictions for Healthy Food Recommender Systems 

  el Majjodi, Ayoub; Khan, Sohail Ahmed; Starke, Alain Dominique; Elahi, Mehdi; Trattner, Christoph (Journal article; Peer reviewed, 2024)

  The visual representation of food has a significant influence on how people choose food in the real world but also in a digital food recommender scenario. Previous studies on that matter show that small change in visual ...

• Résurrection numérique, deuil et données personnelles : décryptage des imaginaires dystopiques et des enjeux éthiques de l’IA dans l’épisode « Be Right Back » de Black Mirror 

  Malet, Marine (Journal article; Peer reviewed, 2024)

  Dans l’épisode « Be right Back » (S02E01) réalisé par Owen Harris et diffusé sur Channel 4 le 11 février 2013, la série télévisée Black Mirror met en scène une intelligence artificielle programmée pour permettre de converser ...

• BabelBot at AraFinNLP2024: Fine-tuning T5 for Multi-dialect Intent Detection with Synthetic Data and Model Ensembling 

  Fares, Murhaf; Touileb, Samia (Chapter, 2024)

  This paper presents our results for the Arabic Financial NLP (AraFinNLP) shared task at the Second Arabic Natural Language Processing Conference (ArabicNLP 2024). We participated in the first sub-task, Multi-dialect Intent ...

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