Strategic Research Programme on Media Economics: Algorithm-Driven Media industries and how they reshape value in small markets
In the context of on-demand distribution and consumption of media content, online delivery platforms rely on a relatively new component in media industries: algorithms. In practice, algorithms facilitate the online curation of large on-demand catalogues (e.g., for streaming services such as Netflix or video-sharing platforms such as YouTube), and, by analysing user data, they offer personalised recommendations for content (e.g., news pieces/topics, series/films to watch, topics/genres to ‘discover’ etc.). Algorithms are not only shaping new business models, for both new platforms and legacy media organisations (newspapers, broadcasters), but they are also notorious for their technological complexity and intentional opacity. Thus, the third SRP in Media Economics focuses on the algorithmization of media industries and the ways in which notions of ‘value’ are being transformed by the use of algorithms.
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 methods will range from established ones that SMIT researchers have a proven track record in, such as diary studies, expert interviews, document analysis, to novel digital science methodologies, such as experiments and data analytics. 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.