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This research project tackled the growing problem of decision fatigue in streaming entertainment platforms, where users spend an average of 20 minutes just deciding what to watch.

Through comprehensive user research with young professionals, I identified that current recommendation systems fail to account for contextual factors and emotional states. Using methods including affinity mapping and iceberg modeling, I uncovered that recommendations should consider not just viewing history but also time of day, current emotional state, cognitive capacity, and social context.

The project identified key gaps in existing platforms and proposed a context-aware recommendation system that could transform how users discover content based on their current situation and needs rather than just past preferences.