Affect analysis for text dialogue in movies

With the surge of services offering video-on-demand through streaming and the increased competition in the field, the need for the provider of the service to be able to fit its content to its users is important. Machine learning can be utilized to in an automatic fashion find user or movie patterns by looking at features from its data.In this project I create a model with weighting schemes to find affective content from small texts and then explore the potential to also do this for movies by extracting affective features from the movies subtitles. The affective content is determined by using a dictionary with affective labeled words to in a Bag-of-Word fashion score sentences by a dimensional approach with three dimensions called Valence, Arousal and Dominance (V,A,D). The project also consist of a data gathering where two separate datasets are gathered with already V,A,D labeled data, one dataset is found online and the other is self-gathered. These datasets are then used for validation of the affective model and to find the best weighting schema. The best weighting schema is then used to determine affective content during the duration of a movie and utilized to find interesting segment in a movie but also to compare movies and find similarities.I find that the performance of my model is somewhat decent with best scores on the dimensions Valence and Arousal and that there are small difference based on which weighting schema is used for the model. I find that the model shows potential in the movie domain, by finding interesting segments in a movie but also finding scene-similarities between movies. It does however have its limitation by not being able to distinguish genres and missing affective content expressed through visual or audio cues. Finally I argue my model could be incorporated into a larger machine learning model to determine similarities in movies or find user patterns but it also requires similar models to determine affective content from the audio and visual in the movi