The development of technology has changed the way viewers consume video contents. With the rising of streaming services, video contents are gathered in one big platform, making them much more accessible than ever before. However, in the meantime, the ever increasing content choices on streaming services overwhelm and frustrate us, reducing our satisfaction with the experience. In addition, as recently as just a few years ago, television was a communal experience. We would watch TV together, on one shared screen. Now, we are isolated when using video streaming services on personal screens.
This project is aimed to enhance viewing experience on streaming service by providing more precise and relevant movie recommendation based on viewer’s social networking, and leveraging video contents as the bridge to develop shared experience and foster greater social engagement.
The outcomes will demonstrate a series of functionalities that allow users to refer to their friend’s viewing activities and reviews as options for movies, open up vivid conversations with friends by easily capturing and sharing memorable scenes from movies, as well as expand social connections based primarily on affinity in movie preferences for greater social engagement and richer viewing experience.
Library of Congress Subject Headings
Streaming video--Social aspects; Recommender services (Information filtering)
Visual Communication Design (MFA)
Department, Program, or Center
School of Design (CAD)
Chen, Wen-Hua, "Leverage social filtering to enhance viewing experience with Amazon Prime Video" (2020). Thesis. Rochester Institute of Technology. Accessed from
RIT – Main Campus