Predicting Movie-elicited Emotions from Dialogue in Screenplay Text: A Study on "Forrest Gump"

Abstract

We present a new dataset of sentences1 extracted from the movie Forrest Gump, annotated with the emotions perceived by a group of subjects while watching the movie. We run experiments to predict these emotions using two classifiers, one based on a Support Vector Machine with linguistic and lexical features, the other based on BERT. The experiments showed that contextual embeddings are effective in predicting human-perceived emotions. Copyright c ©2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).