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.

Predicting movie-elicited emotions from dialogue in screenplay text: A study on “Forrest gump”

Iavarone, Benedetta;
2020

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.
2020
Settore INF/01 - Informatica
7th Italian Conference on Computational Linguistics, CLiC-it 2020
ita
2021
CEUR Workshop Proceedings
CEUR-WS
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11384/134283
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