Recommended content is a big part of many people's everyday lives and shapes users' experience (UX) and media consumption on a daily basis. With a varied amount of knowledge about how algorithms affect people's media consumption, the decision-making process is influenced to varying extents. The focus of this study is therefore to examine the diversity of variations that exist around the perception of YouTube's algorithms and its influence on the users’ experience. We conducted a quantitative study in the form of a questionnaire, as well as semi-structured interviews to answer the questions of how the users assumptions regarding the recommendation algorithm on YouTube affects the user experience. The study suggests that the ignorance that arises as a result of the lack of transparency shown between algorithm and user, contributes to the user experience being influenced by the assumptions. To a large extent, we can see that these approaches depend on the mental models that users have built, which are often based on the assumptions made in the light of users' own experience.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-183896 |
| Date | January 2021 |
| Creators | Eriksson, Hampus, Ekengren, Anton, Askeljung, Valdemar |
| Publisher | Umeå universitet, Institutionen för informatik, Umeå universitet, Institutionen för informatik, Umeå universitet, Institutionen för informatik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | Informatik Student Paper Bachelor (INFSPB) ; 2021.17 |
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