PENGALAMAN KONSUMSI MUSIK PENGGUNA SPOTIFY YANG MENGGUNAKAN PLAYLIST REKOMENDASI BERBASIS ALGORITMA PLATFORM - Zharabib Rizha Moammereta; Nurist Surayya Ulfa (Jurusan Ilmu Komunikasi, FISIP, Universitas Diponegoro, 2026)
The presence of recommendation features on Spotify illustrates the dynamic relationship between users’ music choices and the platform’s guidance. Although recommendation features offer certain conveniences to users, they do not always steer users’ music consumption toward accepting the platform’s curated selections. Each user has a subjective interpretation of their experience using recommendation features, shaped by a process of deep and ongoing reflection. This study employs a qualitative method with a phenomenological approach and the Interpretative Phenomenological Analysis (IPA) technique to understand Spotify users’ subjective interpretations of platform-guided music consumption through personalized playlists. The concepts and theories utilized in this study include digital music consumption, platformization, user agency, and Folk Theories of Algorithms. The results of this study indicate that users’ reflection processes regarding recommended playlists are shaped by three main factors: the purpose of using the feature, negative feelings toward recommendations, and users’ algorithmic knowledge. Furthermore, these reflections give rise to a number of strategies employed by Spotify users to manage their personal music consumption within the recommendation ecosystem. These strategies include rejecting specific recommendations, navigating algorithms, and a tendency to prioritize personal playlists as a means of enjoying music in a more directed, personal, and contextual manner.