MovieBaba is a movie review and discussion community platform designed for movie enthusiasts to record their viewing history, share opinions, and discover new films.
Users can rate movies they have watched, write reviews, participate in discussion topics, and receive personalized recommendations based on their genre preferences and viewing behavior. The platform also provides movie rankings, trending discussions, and detailed movie information through external movie data integrations.
A recommendation system was developed using user ratings and viewing history to identify genre preferences and suggest relevant movies. Statistical analysis of watched films enables personalized recommendations tailored to individual tastes.
The platform combines movie content, user-generated reviews, discussions, comments, and voting systems within a unified architecture. Careful database modeling was required to maintain relationships between movies, users, reviews, and discussion threads.
TanStack Query was used to manage server state efficiently, reducing unnecessary network requests while keeping user-generated content synchronized across the application.
Supabase provided authentication, PostgreSQL database services, and storage capabilities, enabling rapid development while maintaining scalability and data consistency.
MovieBaba evolved into a full-featured movie community platform that combines movie discovery, personalized recommendations, reviews, and social discussions. The project demonstrates experience in full-stack application development, recommendation systems, community platform design, authentication workflows, and modern React architecture.