Algorithms, sharing und selectivity: Fragmentation of audience attention

The explosion of content supply on the Internet gives recipients access to an almost unlimited variety of informative and entertaining content. At the same time, a wide range of different, even non-media pieces of content are competing on convergent technical platforms. Both developments together lead to a flooding of the recipient, who has to make selection decisions more frequently and more far-reaching selection decisions. Numerous navigation aids such as search engines, aggregation portals, but also social networking sites offer their support by pre-selecting and sorting content. These functions are gratefully used, which gives the "new intermediaries" a potentially significant influence on the behavior of users.

This dissertation project investigates the influence of social recommendations, technical recommendation systems and aggregators of popular content on the selection decisions of recipients. The aim is to map fragmentation tendencies in the digital media environment and to identify the main influencing factors. The theoretical framework is a combination of fragmentation and diversity research and the concept of selectivity. Empirically, the work focuses on the evaluation of digital behavioral data (non-reactive measurements).

Project staff:
Dr. Pascal Jürgens