Andra lyssnar även på... : En kvalitativ studie om användarupplevelsen av Spotifys rekommendationssystem.

Detta är en Kandidat-uppsats från Umeå universitet/Institutionen för informatik

Sammanfattning: The overload of content in digital services demands a way to filter the content for each individual user. The solution to this problem has come to be recommendation systems, which creates recommendations after the behavior patterns and preferences of each user. Previous research of recommendation systems tends to focus on the technical sides of the algorithms, and the user's perspective often gets forgotten. Although there's no direct connection between the preciseness of the algorithms and the users experience, instead subjective factors play an important role. This study wants to create a deeper understanding of the user experience of recommendation system in order to help digital services improve their use of these systems and hence their user experience. This study specifically examines how Spotify users experiences the services use of recommendation systems. Spotify is a music streaming service which uses recommendation systems in various functions. A qualitative study has been conducted through surveys, observations and interviews with a targeted audience. While analyzing the collected data recurrent themes were sorted under five categories. Based on recurrent themes we were able to state several conclusions. Problems in the interface design had an impact on the users experience of the functions based on recommendation systems, making interface an important aspect of the user experience of recommendation system. The purpose of using recommendation systems was described as to explore new music, although this purpose is generally not fulfilled. Although users found the recommendations relevant their core purpose was not fulfilled, this shows how significant research of the user perspective is. Lastly practical improvement suggestions are discussed, such as social interactions between users, a higher implementation of collaborative filtering and changes in the interface. 

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