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< Back New policy brief: International versus local VOD 4 Nov 2024 In a new policy brief and webinar, we present the findings of research on motivations of Flemish viewers ⇩ ENGLISH BELOW ⇩ Tijdens een webinar op 31 oktober presenteerde het Proeftuin Project nieuwe inzichten over de streaminggewoonten en voorkeuren van Vlaamse kijkers. Dit zijn de vijf belangrijkste conclusies: 1. Kijken blijft een collectieve activiteit Streaming biedt gepersonaliseerde aanbevelingen, maar kijkgedrag vertoont nog steeds sterke overeenkomsten met het traditionele, lineaire kijkpatroon. Keuzes worden vaak beïnvloed door sociale omgevingen, en samen kijken blijft een waardevolle culturele activiteit. Het ‘watercooler-effect’, waarbij populaire shows gesprekstof opleveren, blijft relevant, zowel voor internationale hits als lokale titels. 2. Lokale platformen lopen achter met personalisatie, maar voldoen aan verwachtingen Internationale platformen zijn sterk in personalisatie, terwijl Vlaamse kijkers vaak al weten wat ze willen zien op lokale platforms zoals VRT MAX en VTM GO. Hoewel deze platformen geavanceerde aanbevelingssystemen missen, slagen ze erin om te voldoen aan de vraag naar specifieke lokale content. De belangrijkste uitdaging blijft het uitbreiden van de catalogus en de gebruiksvriendelijkheid verbeteren. 3. Vlaamse kijkers waarderen lokale content Lokale platformen zijn de voorkeurskeuze voor Vlaamse kijkers die op zoek zijn naar regionale shows, terwijl grote streamingdiensten zoals Netflix over het algemeen worden geassocieerd met internationale content. Deze waardering voor lokale content geeft platformen zoals VRT MAX en Streamz de kans om zich te onderscheiden, vooral voor kijkers die regionale verhalen belangrijk vinden. 4. Streaming en bioscoop bezoek: Complementaire ervaringen Vlaamse kijkers zien streaming en bioscoopbezoek als aanvullend op elkaar. Degenen die veel streamen, gaan ook vaak naar de bioscoop, vooral vanwege de gedeelde ervaring. Hoewel de prijs voor sommigen een drempel blijft, blijft de bioscoop aantrekkelijk vanwege de unieke sociale sfeer. 5. Lokale content leeft, maar internationale content domineert Vlaamse kijkers associëren lokale platformen sterk met regionale content, maar hun kijkgedrag op grote platformen neigt naar internationale series en films. Deze voorkeur voor globaal aanbod vormt het streaminggedrag, maar lokale platformen blijven inspelen op de vraag naar binnenlandse verhalen en ervaringen. Voor een diepgaandere analyse, bekijk de volledige policybrief op de SMIT-website . ___________________________________ During a webinar on October 31, the Proeftuin Project revealed fresh insights into the habits and preferences of Flemish streaming audiences. Here are the five main takeaways: 1. Watching together remains Streaming may allow for individual recommendations, but watching habits still mirror traditional, linear viewing. Choices are often influenced by social settings, and shared viewing remains a strong cultural activity. The “watercooler effect,” where popular shows spark conversations, is still alive, with both international hits and local titles playing a role. 2. Local platforms lag in personalization but meet viewer expectations While international platforms excel at personalization, Flemish viewers often know exactly what they want to watch on local platforms like VRT MAX and VTM GO. These platforms lack sophisticated recommendation systems, yet they succeed in catering to viewers' demands for specific local content. The main challenge remains expanding their catalog while enhancing usability. 3. Flemish viewers value local content Local platforms are the preferred choice for Flemish audiences seeking regional shows, while major streaming services like Netflix are generally associated with international content. This appreciation for local content allows platforms such as VRT MAX and Streamz to distinguish themselves, particularly for viewers who prioritize regional storytelling. 4. Streaming and cinema are complementary experiences Flemish viewers see streaming and cinema as complementary. Those who stream frequently also tend to visit cinemas, mainly for the shared experience. While price remains a deterrent for some, cinemas remain attractive for their unique social environment. 5. Local content thrives, but international content dominates While Flemish audiences strongly associate local platforms with regional content, their actual viewing behavior on major platforms leans towards international series and films. This preference for global content shapes streaming behavior, yet local platforms continue to meet the demand for domestic stories and experiences. For more information the full policy brief is available on the SMIT website (Dutch only). Previous Next

< Back A glimpse into our work-in-progress 12 Feb 2024 Reflections on the research presented at Etmaal On Thursday 8th and Friday 9th February 2024, Hanne Vandenbroucke and Ulysse Maes attended the 26th edition of Etmaal van Communicatiewetenschap in Rotterdam. At this two-day conference, researchers from Communication Sciences in Belgium and The Netherlands unite to present their projects, get feedback from peers, and be inspired by the work of others. They were invited to present their work-in-progress during the Research Escalator. In this blogpost we highlight the key take-aways from their presentations. Multi-stakeholder approach to news personalization - Hanne Vandenbroucke What lies behind the "For you", "Read more" or "See also" sections on the website or mobile app of your favorite news brand? By conducting stakeholder interviews with professionals working in commercial news organizations operating in Flanders: DPG Media, Mediahuis and Mediafin; We aim to map the development and implementation of recommender systems. The key internal stakeholder groups involved in and impacted by news recommender systems are: (1) the newsroom, (2) the technical development, and (3) the commercial business unit. Based on the stakeholder interviews, we are able to build upon the multi-stakeholder framework of Smets et al. (2022) . The preliminary results give insights in the actual decision-making process for recommender development. News organisations started experimenting with a news recommender system on average 3 years ago. The initial process of trial and error had transformed into an ongoing cycle of adjusting the RS design. In practice both the newsroom and the business unit express their objectives, preconditions and concerns to the product owner who aligns the different perspectives and formulates a concrete set of goals. Next, the technology development team will operationalize these objectives into computational metrics and adjust the recommender system design. Performance data is continuously being collected and monitored. A feedback loop set up to communicate the results of the adjusted recommender to the product owner who – together with the data analytics team – derives insights from the data and report back to the business unit and newsrooms. Exploring the influence of misleading explanations on the perceived quality of recommender systems – Ulysse Maes Nowadays, recommender systems are everywhere: you find them on Amazon, on Netflix and Spotify, for example. These algorithmic curation systems help internet users to efficiently navigate through vast amounts of content. While holding clear advantages in terms of user experience, there are some limitations and normative concerns. One of these concerns stems from the limited transparency they provide. This may lead to distrust and frustration. Adding explanations may yield different results, which depend on your objectives. (Tintarev & Masthoff, 2007) suggest seven goals of explainable recommendations: effectiveness, efficiency, satisfaction, scrutability, transparency, trust, and persuasiveness. Note that maximizing for one goal might be beneficial for another (e.g. improving for scrutability- giving users the ability to change the outcomes to their liking- might improve satisfaction). However, optimizing for one goal might also harm other goals. This research specificially dives into the possible conflict between optimizing for persuasiveness and its effects on transparency and trust. By “optimizing for persuasiveness”, we mean creating compelling narratives to persuade users to consume recommended content. For example, when you buy a pair of jeans online, the shop can try to upsell by recommending some white t-shirts and explain the recommendations as “Style advice for the perfect shirt to wear on your new jeans.” A more neutral explanation could be: “Customers also bought.” Persuasion in itself is not problematic, but it might become problematic once it becomes misleading: hiding important information or even lying about the working of the system, or the drivers behind a decision. As explanations are often linked to a conception of transparency, both with end-users and academia, the mere presence of explanations can already lead to increased trust in the system. By crafting compelling but incorrect explanations, it might be possible to manipulate users into consuming certain content, while still giving them a feeling of agency. There are clearly some incentives to create misleading explanations. But do they work? Theory is still inconclusive. While some research mentions the effectiveness of personalized persuasion (Burtell & Woodside, 2023), others highlight the detrimental effects on long-term trust: would platforms really jeopardize this? Another argument against the effectiveness of misleading explanations is that the costs don’t outweigh the benefits – a critique sometimes formulated on explanations in general as well. The field of explainable AI recognizes the immense potential of Large Language Models (LLMs), such as ChatGPT, to generate personalized, dynamic explanations at scale. It has already been shown that these explanations can be more persuasive than human-generated texts. One of the reasons why we do not see LLM-generated explanations popping up everywhere, is because of their tendency to “hallucinate” - to make up plausible, but incorrect narratives. Previous Next

< Back Interface real estate: Amazon Prime and visibility politics van Es, K., & Iordache, C. (2025). Interface real estate: Amazon Prime and visibility politics. Critical Studies in Television , 0 (0). https://doi.org/10.1177/17496020251375211 This paper investigates how Amazon Prime Video’s interface design affects content visibility, specifically analysing the prioritisation of Prime-included versus third-party content. Using the Vignette tool on French accounts, we conducted a mixed-methods analysis of homepage structures, including row hierarchies and title heatmaps across multiple user profiles. We find that while Prime Video shares common strategies with other services (e.g. own content prioritisation and burying the continue watching button), it distinguishes itself with a uniquely dense landing page layout featuring a large number of thumbnails and content rows. This design reveals deeper commercial logics shaped by Amazon’s integrated retail model. Previous Read the article Next

Doe mee aan het onderzoek en krijg een bol.com bon ter waarde van 50 euro! 1 . Jouw mening telt In deze unieke studie van de Vrije Universiteit Brussel en Play Media onderzoeken we hoe jij reclame beleeft. Jouw input helpt ons om de kijkervaring van de toekomst vorm te geven. 2 . Hoe verloopt het onderzoek? Tijdens het onderzoek kijken we naar twee aspecten: we vragen naar jouw persoonlijke ervaringen en we passen de reclameblokken mogelijks aan om te zien wat voor jou het beste werkt. Na je inschrijving ontvang je meer informatie over de volgende stappen. 3 . Beloning voor deelname Als bedankje voor je tijd en waardevolle inzichten ontvang je na afloop van het onderzoek een bol.com cadeaubon ter waarde van €50 als je het hele onderzoek hebt meegedaan. Vragen over het onderzoek? Neem contact op met ons op via jeroen.peeters@vub.be of iris.jennes@vub.be Voornaam Achternaam E-maladres Telefoonnummer E-mail van je Play account Inschrijven Jouw gegevens worden strikt vertrouwelijk behandeld volgens de GDPR-richtlijnen en enkel gebruikt voor dit onderzoek. Bedankt voor je inschrijving, we contacteren je binnenkort! Neem deel aan het onderzoek

< Back Catching the waves: The case of VRT's digital-first audio strategy Van der Elst, P., Iordache, C., & Raats, T. (2025). Catching the waves: The case of VRT’s digital-first audio strategy. European Journal of Communication . https://doi.org/10.1177/02673231251370877 European public service media (PSM) are increasingly embracing strategies that balance digital platform tactics and meeting the public remit. This article addresses how a small market PSM is repositioning itself in a media landscape dominated by global platforms, streaming services and legacy media adopting platformisation strategies. We examine platformisation at the Flemish broadcaster VRT through the lens of its digital audio strategy. The study combines document analysis and expert interviews. Results show a strategic shift towards more focus on user needs and habits; a branding strategy revolving around the VRT parent brand; a necessary yet precarious presence on third-party platforms; a legacy-driven content offering complemented by online-only commissioning; and a firm editorial grip on content curation. VRT's take on these strategic innovations highlights a series of key dilemmas for PSM to reconcile public remit delivery and competitiveness in a platformised media landscape. Public Service Media Previous Read the article Next

< Back Policy Brief on Public Service Media in Belgium 27 Mar 2025 Findings and recommendations on the organisational and cultural challenges facing PSM in Belgium In this new policy brief Tim Raats and Cataline Iordache share results from the latest research conducted during the second year of the PSM-AP project . Their findings show that Public Service Media (PSM) organizations in Belgium, being RTBF (French-speaking) and VRT (Flemish) face growing competition from global tech giants such as Netflix, Apple, Google, and Amazon. This requires a transition into fully digital, online-first broadcasters. While both are integrating digital tools and skills, structural barriers rooted in traditional broadcasting, such as bureaucracy and departmental silos, slow down this transformation. They are adapting their commissioning and distribution strategies to better meet audience needs while maintaining their public service mission and managing brand perception. However, their digital transition differs: VRT is positioning VRT MAX as the central platform for content, whereas RTBF struggles to rebrand Auvio beyond a catch-up service, as linear TV is still dominant for reaching audiences. Their study identifies the following four key factors that shape the way in which both Belgian PSM organizations are managing the rise of internet delivery and increasing competition with international streamers: If you want to learn more about the outcomes of in-depth interviews with employees in both PSM organizations, have a look at the full policy brief here . Previous Next

< Back Aina Errando PhD Researcher aina.errando@vub.be With a background in journalism, she has studied a master’s degree in Political Science: International and European Governance (VUB), an Advanced Master’s in European Integration (BSOG), and a Master’s in Digital and Data Journalism (Nebrija Univeristy). As a PhD researcher in the ALGEPI project (understanding ALGorithmic gatekeepers to promote EPIstemic welfare), she works analysing some of the most pressing challenges facing the media industry today. Her research focuses on algorithmic gatekeepers and media strategies, exploring why and how algorithms are designed to fit and influence media consumption. In an algorithmic media environment, it is crucial to understand which mechanisms help retain or regain trust in media as well as to assess how algorithmic gatekeepers can contribute to or hinder media diversity. Visit my research profile

< Back From Experimentation to Strategy: The Ambidextrous Balancing Act of Developing News Recommender Systems Vandenbroucke, H., & Smets, A. (2025). From experimentation to strategy: the ambidextrous balancing act of developing news recommender systems. Journal of Media Business Studies , 1–28. https://doi.org/10.1080/16522354.2025.2590880 Despite advances in news recommender systems (NRS) research, their application in news organisations remains limited, hampered by practical obstacles and organisational challenges. This study applies the multi-stakeholder framework alongside ambidexterity theory to analyse the complex decision-making dynamics in applying NRS within two large commercial news organisations. Based on 11 in-depth interviews with different stakeholders, two “balancing acts” emerged. The first is stakeholder alignment through two strategies: knowledge management with dummy-proof presentations and “showcasing success” to help increase stakeholder buy-in for NRS. The second balancing act is managing trade-offs between exploration and exploitation in a roadmap developed by the multidisciplinary team of product owners (POs), ensuring a balanced allocation of resources for NRS innovation and optimisation. This research shows how organisational ambidexterity supports successful technology integration and provides insights for implementing emerging technologies in complex multi-stakeholder news media environments. Recommender Systems, Stakeholders, Newsmedia Previous Read the article Next

< Back Wrap-up of the RecSys Summer School 16 Jun 2023 Our key takeaways from the Recommender Systems Summer School in Copenhagen From 12 to 16 June, several researchers from the Media Economics & Policy Unit took part in the Recommender Systems Summer School in Copenhagen. During this Summer School, academics and industry leaders lectured on the practice, research, and state of the art in recommender systems. The lectures covered a broad range of topics from an algorithmic as well as a methodological perspective, including hands-on sessions. This week brought many interesting insights for our strategic research program on recommender systems and this short report highlights some of the key takeaways. Not an algorithm, but a system Recommender systems encompass more than just the algorithm itself. They require the thoughtful implementation of (a combination of several) algorithms that align with specific domain objectives, account for optimal user experience in different contexts, and seek to create mutual value for various stakeholders It is crucial to recognize that there is no one-size-fits-all approach to recommender systems. The strategy employed must be tailored to the specific domain in which the system operates, considering the unique objectives, economic factors, values and challenges inherent to that domain. For instance, in the realm of news, evaluating the system's quality necessitates considerations such as diversity and serendipity, speed and coverage. The recommender system design must consider the overall user experience. This involves understanding the various features and styles influencing users’ interaction with the platform, as well as analyzing the user journey and recognizing the impact of contextual dependencies on their preferences and needs. In both academic literature and practical applications, the primary goal of recommendation systems is to create value. This entails a reciprocal relationship between user values and business values. By addressing user needs and providing quality personalized recommendations that go beyond mere accuracy the system increases short-term engagement. Furthermore, these systems aim to cultivate long-term loyalty and build strong relationships with the target audience. In summary, well-designed recommendation systems enhance user engagement by offering personalized recommendations, optimizing the user experience, reducing information overload, fostering serendipitous discovery, continuously learning and improving, integrating social features, and thereby generate added value for business through increased user satisfaction, retention, and potential revenue growth. End of the artificial clean cut between content? Media mergers are changing the industry. One of the many examples is how RTL XL will become a part of Videoland. The question rises how the video-on demand platforms can blend different content types such as movies, series, TV programs, short clips and livestreams in an appealing way. An answer to that question could be answered by formulating the optimal user experience through recommender systems. Currently, the company is analyzing user behaviour in order to develop models that can be used in online user experiments. A next step will be to start A-B testing to create the optimal recommendation model. The goal of VOD platforms is to have loyal visitors, but it is a metric that moves very slowly. Currently, the recommendation system of the RTL is built up on three different types of recommendations: content-based, popular within the genre and collaborative filtering. Interesting fact: Personalized swimming lanes compared to editorials swimming lanes generate 30 min more viewing time per active user per month. The main goal of “this recommender optimizing project” is to work towards continuous loops. Sequential recommender systems are different in that sense that they convert user’s behavior trajectory into recommended items or services. It takes into account the current and recent preferences of a user for a more accurate recommendations. Implementing this new form of recommender system will be one of the key factors to generate a user interface with “blended content” that answers the customer’s needs. A critical stance in the evaluation of recommenders Being grounded in dominantly quantitative forms of assessment, recommender system evaluation needs to pay sufficient attention to real-world significance of numerical results and to whether outcomes actually make sense in applied cases. For instance, is an overall increase in prediction accuracy of a recommendation an accomplishment when large parts of the user base still receive bad recommendations and their preferences remain ill-defined? A call for qualitative sense-making of quantitative evaluation outcomes was certainly made at the Summer School. Also, research papers that seek to evaluate recommender systems often focus more on (incremental) increases in performance percentages than on a solid basis for their actual evaluation. In terms of relevance for the academic field, consequently, little contributions are made. Papers that are characterised by vagueness and technical complexity thus prevent real progress and cannot form the basis for further research. The lack of valuable longitudinal research in the domain of recommender systems can also be related to this. Lastly, by acknowledging that recommender systems impact not only the intended end-user and that their complex nature implies influences also on those not directly involved, we argue that multiple-stakeholder considerations should be the norm. We realize that the inherent complexity of recommender systems makes this a difficult endeavour. But in our attempts to evade the McNamara fallacy and to research in the most holistic way possible, the aim should always be to keep a multi-stakeholder involvement top-of-mind. Not solely in phases of design or evaluation, but as a constant reflective thought from the outset and throughout. 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 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 Our work-in-progress at DBWRS 2023 18 Dec 2023 Explore our work-in-progress presentations at DBWRS2023 Last week our team attended the first edition of the Dutch-Belgian Workshop on Recommender Systems. DBWRS 2023 proved to be a dynamic event for the exchange of ideas, insights, and ongoing research. Among the highlights were the six compelling work-in-progress posters presented by our researchers. In this blog post, we are excited to share a glimpse into these projects, providing a brief overview of the groundbreaking work our team is currently undertaking. 1. What Will We Be Streaming Tonight? And Why? This project delves into the fascinating world of streaming preferences. The Living Lab project explores the affordances that influence users' choices in content consumption. From binge-worthy series to thought-provoking documentaries, we're unraveling the intricate tapestry of streaming behaviors. 2. Newsroom Realities: An Exploration of Changing Dynamics in News Organizations in Relation to Recommender Systems In a rapidly evolving media landscape, Hanne's PhD-journey investigates the impact of implementing recommender systems on newsroom dynamics. How do different stakeholders wihtin news organizations look at the potential opportunities and risks of recommendations and personalization? 3. Assessing the Potential of Large Language Models for Personalized Explainable Recommendations in Media Large language models have revolutionized natural language processing. In his PhD, Ulysse will explore their potential for personalized and explainable recommendations in the media domain. Uncover the methodologies and insights that pave the way for a more transparent and user-centric recommender system. 4. Intention and Behavior: A Systematic Review of Literature on Users Preferences in Recommendation Systems Understanding users is at the heart of designing effective recommendation systems. Through an systematic literature review, Dongxiao sheds light on the intricate interplay between user intentions and actual behavior. 5. Discovering the Rhythm: The Impact of Online Platform Recommender Systems on Music Discoverability Music is a universal language, and our researchers in the FairMuse project are exploring how online platform recommender systems influence the discoverability of music. From algorithmic playlists to tailored suggestions, we're uncovering the rhythm that shapes users' musical exploration. 6. Gatekeeping in the Digital Age: Newsroom Resistance to News Personalization As news personalization becomes more prevalent, Aina investigates the resistance to recommender systems in newsrooms in Spain as a part of the Algepi-project . These work-in-progress posters showcase the diversity and depth of ongoing research of the SRP Media team. Together, we navigate the ever-changing landscape of recommender systems, digital platforms and streaming services. Previous Next