Emotionally Driven Film Referral System Using Color Psychology

The modern world comprises many forms of entertainment, the most common being movies. Over the past decades, the methods of production, creation, and distribution of movies have greatly advanced. People have a variety of movies to choose from and require a recommendation system to guide them in this process. Emotion-based movie recommendation systems (E-MRS) are ones that recommend movies based on the user's emotions. Emotions are a strong reaction to stimuli and are an intelligent and rational form of behaviour. It is difficult to assess the emotional responses to movies based on the diverse reactions to movies. Colour psychology can be used to detect various emotional states such as happiness, sadness, anger, fear, and excitement. In this paper, a user interface is created where colours are used to represent the user's appropriate emotions, and these emotions are compared with the facial emotion, then the movies will be recommended based on that. A hybrid approach, combining collaborative filtering and content-based filtering, is used to recommend movies. Detection of emotion by face is done using convolutional neural network algorithm.