Akademik Veri Yönetim Sistemi
Gümüşhane Üniversitesi İletişim Fakültesi Elektronik Dergisi, cilt.14, sa.1, ss.933-953, 2026 (TRDizin)
Digital video platforms shape the viewing experience not only through
content selection but also through algorithmic recommendation systems
and personalized interface customizations. This study examines how users
interpret the experience of algorithmic steering within the framework
of Stuart Hall's encoding-decoding model. The research is a qualitative
study conducted using a phenomenological design. Semi-structured
in-depth interviews were conducted online with 15 participants who
actively use digital video platforms. The study sample was created using
snowball sampling, and the interviews were recorded and transcribed.
The data were analyzed using qualitative content analysis in MAXQDA, and
the codes were converted into themes. The findings show that
algorithmic recommendations serve as a guide that facilitates the
decision-making process and saves time for some users. However, the fact
that recommendations lead to repetitive content and fail to meet
expectations reveals algorithmic errors and a vicious cycle. While the
promise of personalization can yield a positive experience for some
users through recognition and a sense of being special, others perceive
this process as directed and are concerned about surveillance,
developing a more distant relationship with the platform. Technical
limitations such as subtitle visibility and interface density can
complicate the viewing experience, potentially driving some users to
alternative sources. Consequently, the study reveals that algorithmic
steering creates a tension between functional convenience and loss of
control in the user experience, with users developing varying
interpretations across dominant, negotiated, and oppositional reading
positions.