< Back Impacts of AI on Music Consumption and Fairness Henry, A., Wiratama, V., Afilipoaie, A., Ranaivoson, H., & Arrivé, E. (2024). Impacts of AI on Music Consumption and Fairness. Emerging Media, 0(0). https://doi.org/10.1177/27523543241269047 The algorithmic systems utilized by music streaming services have the potential to positively influence individual choices by promoting new artists, but they are also often accused of perpetuating biases. In this research note, we aim to explore the impact of these platforms’ AI-based algorithms on fairness in music consumption. To address this question, we adopt a multidimensional approach that considers the legal, economic, and algorithmic dimensions of fairness. This approach is applied to our EU Horizon Europe Fair MusE project, which advocates for a fairer music ecosystem. However, it should be noted that we propose a tool to score output (playlists) based on fairness models instead of directly altering the algorithms. Data from end users, data brokers, and open-source databases will inform the model, while the processing of the data is aimed at providing users with insights into algorithmic biases and empower them to influence the output. Acknowledging this aspect, this research note serves as a prelude to highlight the need for increased transparency and explainability of algorithms. Furthermore, we seek to inform policy interventions that promote fairness, particularly regarding data sharing between creators and platform providers. Such interventions would foster trust among stakeholders and benefit both users and businesses. Platforms Previous Read the article Next

< Back Platforms and Exposure Diversity: Towards a Framework to Assess Policies to Promote Exposure Diversity Ranaivoson, H. R., & Domazetovikj, N. (2023). Platforms and Exposure Diversity: Towards a Framework to Assess Policies to Promote Exposure Diversity. Media and Communication , 11 (2), 379-391. https://doi.org/10.17645/mac.v11i2.6401 The fragmentation of consumption and algorithms’ increasing impact on how content is recommended and displayed makes it even more important to analyse and promote exposure diversity, i.e., the extent to which audiences are exposed to, discover, and engage with diverse content. Although there is a growing literature addressing how to define media diversity in the context of the challenges posed by platformisation, this article translates the normative dimensions into a framework for operationalising exposure diversity into a tangible policy goal, taking into account datafication and its consequences in terms of increasing data requirements towards platforms. The main objective of this study is to analyse initiatives to assess exposure diversity in the platform era and to discuss how such assessment could be improved, particu‐ larly for policy initiatives. This involves addressing several challenges of existing approaches for the assessment of exposure diversity related to defining an appropriate frame of reference, determining the degree of diversity required, dealing with data transparency issues, and promoting user autonomy. To achieve this, we propose a framework for analysing initiatives aimed at assessing and promoting exposure to media diversity. Our framework is composed of four key features: measures (type of initiative), metrics (quantifying exposure diversity), data collection methods, and data requirements. We apply this framework to a set of 13 initiatives and find that policy initiatives can benefit from adopting metrics based on distances and experimenting with data collection methods. Platforms Previous Read the article Next

< Back 16 May 2026 This book presents a comprehensive empirical examination of how global services like Netflix, Disney+, and Amazon Prime Video transform European media streaming Streaming Europe explores how global streaming services like Netflix, Disney+, and Amazon Prime Video have reshaped the audiovisual landscape across Europe. Since Netflix’s arrival in 2012, the European media environment has undergone a rapid transformation, affecting every level of the industry—from production and distribution to policy and audience engagement. This book offers the first comprehensive, empirical, and comparative examination of these changes across different European markets. Written by a team of leading media scholars, it balances accessible analysis with evidence-based insights to examine how streamers have altered production practices and business models, shifted established power dynamics, and challenged long-standing broadcasting legacies. The book examines global streamers’ market-entry strategies, the use of diversity and inclusion as competitive positioning, and the tensions between producers over rights retention and local authenticity. It analyses how public and commercial broadcasters across large and small European markets have both emulated Netflix and sought to differentiate themselves from US streamers, and how governments have responded with a patchwork of policy tools such as prominence regulation, quotas, and investment obligations, raising questions about their long-term effectiveness. Finally, it explores how different genres—including teen drama, documentary, European film, scripted television, and web series—both shape and are shaped by global streamers’ evolving strategies. With its strong foundation in research and pan-European scope, Streaming Europe goes beyond single-country perspectives to present a timely and nuanced understanding of how the streaming revolution is shaping Europe’s cultural industries. It will be highly relevant to researchers in the field of media industries, media economics, audiovisual industries and media policy. The Open Access version of this book is available at Taylor and Francis . 9781040574577 .pdf Download PDF • 4.76MB Previous Next NEW BOOK: Streaming Europe

< Back GenUI(ne) CRS: UI Elements and Retrieval-Augmented Generation in Conversational Recommender Systems with LLMs Maes, U. , Michiels, L. & Smets, A. , (8 Oct 2024). GenUI(ne) CRS: UI Elements and Retrieval-Augmented Generation in Conversational Recommender Systems with LLMs. Proceedings of the 18th ACM Conference on Recommender Systems. Bari: ACM , p. 1177-1179 Previous research has used Large Language Models (LLMs) to develop personalized Conversational Recommender Systems (CRS) with text-based user interfaces (UIs). However, the potential of LLMs to generate interactive graphical elements that enhance user experience remains largely unexplored. To address this gap, we introduce "GenUI(ne) CRS," a novel framework designed to leverage LLMs for adaptive and interactive UIs. Our framework supports domain-specific graphical elements such as buttons and cards, in addition to text-based inputs. It also addresses the common LLM issue of outdated knowledge, known as the "knowledge cut-off," by implementing Retrieval-Augmented Generation (RAG). To illustrate its potential, we developed a prototype movie CRS. This work demonstrates the feasibility of LLM-powered interactive UIs and paves the way for future CRS research, including user experience validation, transparent explanations, and addressing LLM biases. Recommender Systems Previous Read the article Next

< Back 8 Oct 2024 Our contributions to the 18th ACM Conference on Recommender Systems From 14 until 18 October 2024, the 18th ACM Conference on Recommender Systems takes place in Bari, Italy. Our SRP Media researchers have various contributions to this conference, as well as the preceding ACM Europe School on Recommender Systems . ACM Europe School on Recommender Systems 2024 During the ACM Europe School on Recommender Systems, leaders in the field give lectures on the practice, research, and state of the art in Recommender Systems. This year, there will be 120 attendees among which 90 students. Click here for the full program . On Tuesday 8 Octobe r, Lien Michiels will teach a lecture on Best Practices for Offline Evaluation . On Friday 11 October, Annelien Smets lectures a course on Digital Economics and Recommender Systems . The ACM Europe School on Recommender Syste ms is organized by Ludovico Boratto (University of Cagliari, Italy) , Cataldo Musto (University of Bari, Italy) , and Fedelucio Narducci (Polytechnic University of Bari, Italy) . How to Evaluate Serendipity in Recommender Systems: the Need for a Serendiptionnaire During the Doctoral Symposium , Brett Binst will present his work from the Serendipity Engine project. Recommender systems can assist in various user tasks and serve diverse values, including exploring the item space. Serendipity has recently received considerable attention, often seen as a way to broaden users’ tastes and counteract filter bubbles. However, the field of research on serendipity is fragmented regarding its evaluation methods, which impedes the progress of knowledge accumulation. This research plan proposes two studies to address these issues. First, a systematic literature review will be conducted to provide insights into how serendipity is currently studied in the field. This review will serve as a reference for novice researchers and help mitigate fragmentation by presenting a thorough overview of the field. This systematic literature review has already revealed a significant gap: the lack of a validated, widely accepted method for evaluating serendipity. Therefore, the second part of this research plan is to develop a validated questionnaire, the serendiptionnaire, to measure serendipity. This tool will provide a ground truth for evaluating serendipity, aiding in answering fundamental questions within the field and validating offline metrics. GenUI(ne) CRS: UI Elements and Retrieval-Augmented Generation in Conversational Recommender Systems with LLMs [demo] During the poster session on Tuesday, Ulysse Maes will present joint work with Lien Michiels and Annelien Smets . Previous research has used Large Language Models (LLMs) to develop personalized Conversational Recommender Systems (CRS) with text-based user interfaces (UIs). However, the potential of LLMs to generate interactive graphical elements that enhance user experience remains largely unexplored. To address this gap, we introduce “GenUI(ne) CRS,” a novel framework designed to leverage LLMs for adaptive and interactive UIs. Our framework supports domain-specific graphical elements such as buttons and cards, in addition to text-based inputs. It also addresses the common LLM issue of outdated knowledge, known as the “knowledge cut-off,” by implementing Retrieval-Augmented Generation (RAG). To illustrate its potential, we developed a prototype movie CRS. This work demonstrates the feasibility of LLM-powered interactive UIs and paves the way for future CRS research, including user experience validation, transparent explanations, and addressing LLM biases. It’s (not) all about that CTR: A Multi-Stakeholder Perspective on News Recommender Metrics During the poster session on Thursday, Hanne Vandenbroucke will present joint work with Annelien Smets . Recommender systems are increasingly used by news media organizations. Existing literature examines various aspects of news recommender systems (NRS) from a computational, user-centric, or normative perspective. Yet research advocates studying the complexities of real-world applications around NRS. Recently, a multi-stakeholder approach to NRS has been adopted, allowing to understand different stakeholder perspectives on NRS development and evaluation within the news organization. However, little research has been done on the different key performance indicators (KPIs) and metrics considered valuable by different stakeholders. Based on 11 interviews with professionals from two commercial news publishers, this paper demonstrates that stakeholders prioritize distinct KPIs and metrics related to the reach-engagement-conversion-retention funnel. The evaluation of NRS performance is often limited to short-term metrics like CTR, overlooking the multiplicity of stakeholders involved. Our findings reveal how different purposes, KPIs, and metrics are valued from the journalistic, commercial, and tech logic. In doing so, this paper contributes to the multi-stakeholder approach to NRS, advancing our understanding of the real-world complexity of NRS development and evaluation. Navigating Discoverability in the Digital Era: a Theoretical Framework During the MuRS: Music Recommender Systems Workshop 2024 , Rebecca Salganik will present joint work with Valdy Wiratama , Heritiana Ranaivoson and Adelaida Afilipoaie (FairMuse). The proliferation of digital technologies in the distribution of digital content has prompted concerns about the effects on cultural diversity in the digital era. The concept of discoverability has been presented as a theoretical tool through which to consider the likelihood that content will be interacted with. The multifaceted nature of this broad theme has been explored through a variety of domains that explore the ripple effects of platformization, each with its own unique lexicography. However, there is yet to be a unified framework through which to consider the complex pathways of discovery. In this work we present the discovery ecosystem, consisting of six individual, interconnected components, that encompass the pathway of discovery from start to finish. Workshop on Normative Design and Evaluation of Recommender Systems (NORMalize) On October 18, Lien Michiels is co-organizing t he Second Workshop on Normative Design and Evaluation of Recommender Systems. Previous Next The RecSys Conference 2024

< Back Annelien Smets Research Professor Annelien.Smets@vub.be Annelien is a senior researcher at SMIT in the Media Economics and Policy unit. Her research centers around personalization and recommender systems, and their value in media markets. Annelien holds a PhD in Media and Communication Studies (VUB) on the topic of serendipity in recommender systems and smart cities. She holds a master’s degree in Information Management (2016) and Artificial Intelligence (2017) from KU Leuven. Currently, Annelien is Research Professor at Vrije Universiteit Brussel, where she teaches courses on media economics, digital economics, digital business models, and digital innovation management. She is also co-chair of the Serendipity Academic Researchers Network, part of the Serendipity Society. Visit my research profile

< Back 15 Sept 2023 Exploring Power Dynamics in Digital Platform Markets: A Pragmatic Approach to Normative Recommender Systems We are excited to share that our research team has contributed a paper to the first workshop on Normative Design and Evaluation of Recommender Systems (NORMalize), co-located with the 17th ACM Conference on Recommender Systems in Singapore. Our paper, titled "Towards a Pragmatic Approach for studying Normative Recommender Systems: exploring Power Dynamics in Digital Platform Markets" examines two key economic dynamics prevalent in digital media markets that challenge the development of normative RSs. The first hurdle focuses on the susceptibility of digital platforms to lock-in and monopolization due to network effects, skewing the power balance towards system providers. The second hurdle delves into the "attention economy" and the engagement-centric logic in RS design. This logic, while successful in boosting engagement, might compete with explicit or long-term user objectives We illustrate the real-world significance of these dynamic with insights from the domains of video-on-demand and news media. Furthermore, by offering policy recommendations we wish to address the normative challenges that arise in RS design. PhD researcher Hanne Vandenbroucke will be presenting this paper during the NORMalize workshop on Tuesday, September 19. Previous Next New publication: NORMalize Workshop (@ RecSys23)

< Back Exploring Ethical and Regulatory Challenges of AI Integration in European Union Newsrooms Lefèvre, B., Errando, A., Afilipoaie, A., Ranaivoson, H., & Wiart, L. (2025). Exploring ethical and regulatory challenges of AI integration in European Union newsrooms. Media Studies , 16 (31), 31-55. Artificial Intelligence (AI) has significantly reshaped the news media landscape in the fast-evolving digital ecosystem. While recent legislative measures and industry self-regulation initiatives have emerged to address AI’s implications, the ethical challenges associated with its adoption in European Union (EU) newsrooms and the ways news media organisations navigate regulatory frameworks and internal initiatives remain underexplored. This study aims to bridge this gap by examining the conditions under which AI tools are integrated into media organisations from both organisational and regulatory perspectives. Drawing on an analysis of 30 key documents and 41 in-depth interviews with media professionals and regulatory experts across three EU markets, the study uncovers key findings: a limited discourse on AI use in media organisations, significant disparities in AI implementation practices, and an absence of clear, actionable regulatory guidelines for addressing considerations in AI-driven news content. Platforms Previous Read the article Next

< Back Public service algorithms: Balancing the scales between public mission and market pressures at the BBC and VRT. Iordache, C., Martin, D., & Johnson, C. (2025). Public service algorithms: Balancing the scales between public mission and market pressures at the BBC and VRT. MedieKultur: Journal of Media and Communication Research, 40(78), 59-80. https://doi.org/10.7146/mk.v40i78.147182 The public service media (PSM) shift to digital-first strategies has generated a rethinking of priorities in content production and distribution. This not only involves the integration of algorithms for the curation of their video-on-demand portals, but also a far-reaching reform at the organisational level. As personalisation through recommender systems is increasingly popularised by commercial streaming services, PSM are faced with a balancing act between market pressures and fulfilling their public mission. This article contributes to this discussion by investigating how public service algorithms are developed in practice in the cases of the BBC (UK) and VRT (Flanders-Belgium), and how their implementation is guided by the organisations’ remits. Through document analysis and semi-structured interviews conducted in 2024 with 16 PSM representatives, we discuss the ways in which market, policy, and organisational contexts inform the use of algorithms by the two organisations and suggest the need for a re-theorisation of public service algorithms. Public Service Media Previous Read the article Next

< Back Lien Michiels Postdoctoral Researcher lien.michiels@vub.be Lien Michiels is a Postdoctoral Researcher at imec-SMIT, Vrije Universiteit Brussel and the Adrem Data Lab in the Department of Computer Science at the University of Antwerp. Her research focuses on diversity, discovery and filter bubbles in recommender systems. Previously, she combined her PhD research with her work as a Machine Learning Engineer at Froomle , who provide their recommendation platform as a service to media companies around the globe. She obtained a master's degree in Mathematical Engineering at the KULeuven in 2017. Visit my research profile

< Back Dongxiao Li PhD Researcher dongxiao.li@vub.be We are surrounded by a technologically evolving media world where journalism agencies and media firms are increasingly utilizing innovative technologies like artificial intelligence(AI) to improve the production efficiency and meet our personalized requirements. For a media organization, how to use the technologies to optimize the informative value and its commercial benefits? And for the media industry, how to reach a win-win situation among the main stakeholders including the media firms, the users, the technology developers, and the government, so as to boost the social welfare? Those questions intrigued me to carry out researches on illustrating the relations between the technology, the media industry and the human at different socioeconomic dimensions by both qualitative methods like interview and case study, and quantitative approaches including survey and online data analysis. After achieving the Bachelor’s degree of Economics (Shandong University, China), I worked as an overseas engineering project manager for years in other countries like India and Malaysia, which helped me gain the ability of project management as well as the vision of inter-culture communications. Then I found my enthusiasm in media study and pursued the Master’s Degree of Communication (Tsinghua University, China) with the thesis on AI adoption in the media and creative industry. Having an educational background where economics and communication converge, I am also interested in the economic communication, especially on how the business news could be better accepted via digital technologies like AI and VR. Visit my research profile

< Back The platformization of Public Service Media. A comparative analysis of five BVOD services in Western and Northern Europe Iordache, C., & Raats, T. (2023). The platformization of Public Service Media. A comparative analysis of five BVOD services in Western and Northern Europe. International Journal of Media and Cultural Politics , 19 (1), 3-22. https://doi.org/10.1386/macp_00070_1 Recent developments in the media industries have signalled the need for public service media (PSM) organizations to reposition themselves in order to reach audiences, and also secure financial sustainability and programming rights. In repositioning themselves, PSM have increasingly embraced some of the core characteristics of platforms by developing a central video-on-demand (VOD) service as portal to PSM services, investing in exclusive content and using data to create richer user experiences and gain insights into audience practices. However, this ‘platformization’ process comes with both challenges and opportunities to reach the public service remit. This article conducts an analysis of the on-demand portals of PSM, to uncover how platformization is reshaping the PSM core remit and values, and how these are transposed in online services and offerings. The research employs a comparative case study analysis of five VOD services of PSM in Western and Northern Europe: Belgium-Flanders (VRT.NU), BelgiumWallonia (RTBF Auvio), Finland (Yle Areena), Ireland (RTÉ Player) and Norway (NRK TV). The results discuss three main categories: interfaces and features, strategies for catalogue and content curation, and tools for discoverability and prominence. Platforms, Public Service Media Previous Read the article Next