The explosion of content on the internet gives users access to a virtually unlimited variety of informative and entertaining material. At the same time, a wide variety of offerings – including non-media content – compete on convergent technical platforms. Taken together, these two developments result in users being inundated with information, forcing them to make selection decisions with ever-increasing frequency and scope. Numerous navigation aids – such as search engines, aggregation portals and social networking sites – offer their support by pre-selecting and sorting content. These functions are gratefully utilised, which grants the ‘new intermediaries’ a potentially significant influence over users’ information behaviour.
This doctoral thesis project investigated the influence of social recommendations, technical recommendation systems and aggregators of popular content on recipients’ selection decisions. The aim was to map trends towards fragmentation in the digital media environment and to identify the key influencing factors. The theoretical framework combines research on fragmentation and diversity with the concept of selectivity. Empirically, the study relies on the analysis of digital behavioural data (non-reactive measurements).
Project team members:
