We present a new dataset of sentences 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"
Felice Dell'Orletta
2020
Abstract
We present a new dataset of sentences 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.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | - |
| dc.authority.people | Benedetta Iavarone | it |
| dc.authority.people | Felice Dell'Orletta | it |
| dc.collection.id.s | 71c7200a-7c5f-4e83-8d57-d3d2ba88f40d | * |
| dc.collection.name | 04.01 Contributo in Atti di convegno | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.date.accessioned | 2024/02/20 22:45:57 | - |
| dc.date.available | 2024/02/20 22:45:57 | - |
| dc.date.issued | 2020 | - |
| dc.description.abstracteng | We present a new dataset of sentences 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. | - |
| dc.description.affiliations | Scuola Normale Superiore, Pisa; Istituto di Linguistica Computazionale "Antonio Zampolli", CNR, Pisa; | - |
| dc.description.allpeople | Iavarone, Benedetta; Dell'Orletta, Felice | - |
| dc.description.allpeopleoriginal | Benedetta Iavarone, Felice Dell'Orletta | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 2 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/400968 | - |
| dc.language.iso | eng | - |
| dc.relation.conferencedate | 01-03/03/2021 | - |
| dc.relation.conferencename | Seventh Italian Conference on Computational Linguistics (CLiC-it 2020) | - |
| dc.relation.conferenceplace | online | - |
| dc.subject.keywords | natural language processing | - |
| dc.subject.keywords | affective computing | - |
| dc.subject.singlekeyword | natural language processing | * |
| dc.subject.singlekeyword | affective computing | * |
| dc.title | Predicting movie-elicited emotions from dialogue in screenplay text: A study on "Forrest Gump" | en |
| dc.type.driver | info:eu-repo/semantics/conferenceObject | - |
| dc.type.full | 04 Contributo in convegno::04.01 Contributo in Atti di convegno | it |
| dc.type.miur | 273 | - |
| dc.type.referee | Sì, ma tipo non specificato | - |
| dc.ugov.descaux1 | 450785 | - |
| iris.orcid.lastModifiedDate | 2024/04/04 14:18:01 | * |
| iris.orcid.lastModifiedMillisecond | 1712233081187 | * |
| iris.sitodocente.maxattempts | 2 | - |
| Appare nelle tipologie: | 04.01 Contributo in Atti di convegno | |
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