This master's thesis is a qualitative study on the impact of the platformization of the music
industry on students’ listening habits. It analyses the changes brought about by streaming
services in terms of access to music, personal preferences, and algorithmic recommendations.
The purpose of the research is to explore the frequency and intensity of streaming services
use, their influence on music discovery, the differences between listening to manually curated
and algorithmically generated playlists, and users’ satisfaction with them. The study employs
the methods of media diaries and focus groups. The findings reveal that differences in the use
of streaming services are shaped by routines, moods, personal preferences, and social
circumstances. Participants often discover new music through algorithms, but do not fully
trust them, complementing algorithmic suggestions with their own initiative and
recommendations from others. Participants do not strictly choose between manually created
and algorithmically generated playlists; rather, their use reflects a kind of dialog between the
two. Participants express a stronger emotional connection and consequently satisfaction with
manually created playlists, while they perceive algorithms as tools for recommendations. This
research contributes to a deeper understanding of the relationship between technology, culture
and contemporary ways of music consumption.
|
