The Impact of Recommendation Systems on User Experience in Digital Platforms: Netflix, Amazon Prime Video, and Disney+
Öz
Netflix, Amazon Prime Video, and Disney+ are global streaming platforms that reach millions of users, offering a wide variety of content and easy accessibility. To enhance user experience, these platforms utilize advanced algorithms and recommendation systems. This study examines the recommendation systems of Netflix, Amazon Prime Video, and Disney+ and their impact on user experience based on data collected from social media, news sources, blogs, and forums. Online streaming platforms use AI-powered recommendation algorithms to prevent users from getting lost in the vast content library. However, their effectiveness and the resulting user satisfaction directly shape the user experience. The study employs a descriptive content analysis method, collecting 153 data points for Netflix, 176 for Amazon Prime Video, and 176 for Disney+ via the Mention application. These data are analyzed under five main themes: General Perception, User Interactions, Perception in News Sources, Criticisms of Algorithms, and Engagement with Popular Content. Findings indicate that personalized recommendation mechanisms facilitate content discovery and increase time spent on the platform. However, repetitive or irrelevant recommendations reduce user satisfaction. While some Netflix users find the recommendations effective, others argue that the system struggles to adapt to personal preferences. Similarly, some users consider Amazon Prime Video’s recommendation algorithms accurate, but issues with repetitive suggestions are frequently reported. Disney+, on the other hand, generates satisfaction by promoting content based on its strong brand franchises, but faces criticism for the limited recommendations of niche productions.
Anahtar Kelimeler
recommendation systems, user experience, digital platforms, ai algorithms, content personalization
Kaynakça
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