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< Back How Should We Measure Filter Bubbles? Michiels, L., Vannieuwenhuyze, J., Leysen, J., Verachtert, R., Smets, A., & Goethals, B. 2023. How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News. In Proceedings of the 17th ACM Conference on Recommender Systems. News media play an important role in democratic societies. Central to fulfilling this role is the premise that users should be exposed to diverse news. However, news recommender systems are gaining popularity on news websites, which has sparked concerns over filter bubbles. More specifically, editors, policy-makers and scholars are worried that these news recommender systems may expose users to less diverse content over time. To the best of our knowledge, this hypothesis has not been tested in a longitudinal observational study of real users that interact with a real news website. Such observational studies require the use of research methods that are robust and can account for the many covariates that may influence the diversity of recommendations at any given time. In this work, we propose an analysis model to study whether the variety of articles recommended to a user decreases over time in such an observational study design. Further, we present results from two case studies using aggregated and anonymized data that were collected by two western European news websites employing a collaborative filtering-based news recommender system to serve (personalized) recommendations to their users. Through these case studies we validate empirically that our modeling assumptions are sound and supported by the data, and that our model obtains more reliable and interpretable results than analysis methods used in prior empirical work on filter bubbles. Our case studies provide evidence of a small decrease in the topic variety of a user's recommendations in the first weeks after they sign up, but no evidence of a decrease in political variety. Recommender Systems Previous Read the article Next

< Back Serendipity Engine SBO We increasingly rely on algorithmically generated recommendations to navigate in both online and offline contexts: listening to music on streaming platforms, reading news online, or following recommendations about activities and events in your favorite city. These recommender systems help us dealing with the abundance of available information, but at the same time raise questions about their impact on individual citizens and society. Many advocate for designs for serendipity in recommenders, but what does this mean in practice? While serendipity is generally understood as a beneficial design principle ought to deliver societal value, putting it into practice still presents major challenges. The Serendipity Engine project sets out to address these challenges and support societal stakeholders in designing recommender systems to foster serendipity in public contexts. Researchers on this project Lien Michiels Postdoctoral Researcher Brett Binst PhD Researcher Annelien Smets Research Professor Consortium partners SBO_ IDLAB.png SBO_ ADREM.png SBO_ IMEC.png SBO_ IDLAB.png 1/3 Tags Recommenders, Artificial Intelligence, Smart City, Diversity and Serendipity Previous Next

About SRP Media SRP Media represents the third Strategic Research Programme on media economics at imec-SMIT, Vrije Universiteit Brussel . Its focus lies on understanding algorithm-driven media industries and how they reshape value in small markets. SRP Media c lusters four PhD trajectories and affiliated research projects that deal with Streaming, Recommenders and Platformization in European Media Industries. By doing so, SRP Media aims to foster collaborations and knowledge exchanges across several national and international research projects, and to function as one centralised hub towards external stakeholders. Research projects Streaming, Recommenders and Platformization in European Media Industries The research is conducted within the broader field of media and communication studies, more particularly in the research fields of media economics, political economy, innovation studies, and media policy. The importance of the research is confirmed by existing academic research, current media company practices, and ongoing policy developments in the field. Recent academic research has already been exploring the topic of algorithms in media industries. However, this body of work remains limited, mainly due to the ongoing changes in algorithm use, as well as the limited data publicly available on how algorithms and content recommendations are made in practice. In order to contribute to scientific evidence on the topic, as well as to industry- and policy-related debates and developments, the SRP follows three main research industries, namely news media, public service media, and global and domestic streaming platforms. Each industry will be analysed from four perspectives: media companies, media content, media audiences, and media policy. It also aims to analyse the interplay between the three, to identify their effects on audience consumption, and the ways in which algorithms are used and regulated. The research combines qualitative and quantitative methodology and specifically focuses on small media markets. It also applies case studies, both individually and in comparative analyses, either between different media service providers, or between different EU Member States. The programme will provide media stakeholders with the necessary knowledge on the usage and effects of algorithms on media production, distribution, and consumption. The findings will also help policymakers to formulate legislation that will accurately measure and efficiently regulate the implementation and use of algorithms and recommender systems. Principal Investigators Pieter Ballon Supervisor Tim Raats Supervisor / Track Lead Annelien Smets Track Lead Wendy Van den Broeck Track Lead Meet our team You might also be interested in ... ... fellow knowledge hubs at imec-SMIT, Vrije Universiteit Brussel related to media and technology. Nieuwsgebruik.be Mediapunt Mediawijs Knowledge Center Data & Society

< 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 Rethinking Transparency in Public Service Media: a multidimensional framework for better governance Van den Bulck, H., Horowitz, M., & Raats, T. (2025). Rethinking Transparency in Public Service Media: a multidimensional framework for better governance. Frontiers in Communication , 10. https://doi.org/10.3389/fcomm.2025.1569363 Transparency has become a cornerstone of public service media (PSM) governance yet it remains inconsistently understood and applied. Increased scrutiny from various stakeholders has resulted in a need for actionable and meaningful transparency. Scholarly evidence highlights transparency’s benefits and risks, including potential misuse, as illustrated with current examples from Finnish PSM organization Yle and tVRT in Flanders (Belgium). This brief provides a multidimensional framework for actionable transparency efforts that allow PSM to move beyond ad hoc, reactive and partial approaches by elaborating key dimensions of transparency about what, when, how, by whom and to whom, transparency is required. Recommendations include fostering transparency practices that are meaningful and resistant to weaponization and politicization, developing participatory governance models, and leveraging transparency as a tool for organizational resilience. Public Service Media Previous Read the article Next

< Back Public Service Media in the Age of Platforms PSM-AP Public service media (PSM) organizations have to compete with global streaming services (e.g. Netflix and YouTube), for audiences, revenue and talent. They have had to develop new on-demand services and online content that can only be delivered through the online systems owned by global platforms such as Google, Apple and Amazon. The PSM-AP project asks how PSM organisations, and the regulators and policymakers that legislate for and enforce their remits, are adapting to this new platform age, and how their responses might be altering the social and cultural values of PSM and its ability to operate in the public interest. It focuses on television, which remains at the heart of PSM. It asks how the new environment within which PSM organisations are operating might affect the values that underpin the production and distribution of TV programmes by PSM organizations, and the policy debates and regulatory structures that shape the remits and structures within which PSM organizations operate. The project will compare data gathered within and across six countries and 12 PSM organizations: Belgium (RTBF, VRT), Canada (CBC), Denmark (DR, TV 2), Italy (RAI), Poland (TVP), UK (BBC, Channel 4, S4C, ITV, Channel 5). Researchers on this project Catalina Iordache Guest Professor Tim Raats Associate Professor Consortium partners Aarhus University University of Leeds University of Warsaw Aarhus University 1/5 Tags Platforms, Media Policy Previous Next

< 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

< Back Hanne Vandenbroucke PhD Researcher hanne.vandenbroucke@vub.be Hanne Vandenbroucke joined imec-SMIT-VUB in May 2023 as a PhD- researcher on the topic of recommender algorithms and news personalization in the Flemish news media industry. She followed a unique Bachelor’s trajectory combining Languages and Linguistics with Communication Sciences at KU Leuven. I have completed the Master’s degree in Communication Sciences cum laude at KU Leuven and extended this master with an extra semester abroad at Universidad Camilo José Cela in Madrid. After graduating Hanne gained experience working as a marketing manager in the field of digital education. Visit my research profile

< 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 Public Service Media and Platformization Pieter Van der Elst PhD Researcher This part of the SRP research project aims to develop in-depth knowledge on how an increasingly algorithmized media industry compels European Public Service Media (PSM) to alter their operational and value-related strategies. During a time period of 4 years, we will scrutinize how PSM’s part in the media value chain is affected and what that means for the company, the content and the end-user. A first phase of the research focuses on the organizational side of PSM. More specifically, we concentrate on the case of Flemish public broadcaster VRT and how they are operationalizing a digital and user-first approach in their digital audio strategy. Complementary analysis of the decision-making behind this organizational shift will be key to developing a thorough understanding of what it means for a public legacy media player to adapt to the ever-changing industry it operates in. In later stages of the project, our focus will shift towards what said transition implies for PSM on the levels of content production, distribution and the societal core values imbued. This part of the research will also broaden our scope geographically by including scrutiny of other European PSM organizations and how their methods compare to one another. Examinations of audience perspectives will conclude our research journey and provide us with indispensable insights on the topic. Through this research programme we aim to consolidate our understandings on algorithm-driven media operations and media-economics and media policy oriented PSM-research, not only serve the academic community, but also to provide small market PSM-organizations with tools to better understand and integrate algorithms, and assist policymakers in developing ways of regulating and measuring the impact of algorithms on media output and audience reach. Publications Catching the waves: The case of VRT's digital-first audio strategy 02/09/2025 Challenges and requirements for implementing due prominence: aligning stakeholder interests in Flanders 18/07/2025 Towards a Pragmatic Approach for studying Normative Recommender Systems 18/09/2023 Supervisors Catalina Iordache Guest Professor Tim Raats Associate Professor Related news 2 Report Published: How to Ensure Visibility and Prominence for Media Services of General Interest in Flanders Commissioned by the Flemish Minister of Media, this research report investigates findability, discoverability, and due prominence for audiovisual and auditive media services. 2 Ciao from EMMA in Rome! Our presentations at the emma Conference 2025 2 Media Industries Conference, London An overview of our presentations at Media Industries in London Previous Next

< 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 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