Exploring Personality Traits: A Big Five Profiling of Fictional Movie Characters

In this article, we explore the viability of establishing a personality profiling system rooted in the Big Five model for movie characters. We curated a corpus sourced from movie scripts and proceeded to evaluate several traditional machine learning models alongside an LSTM model. Our findings indicate that traditional machine learning outperforms the LSTM model in this context.

Authors

Publication Details

Journal
Computación y Sistemas
Published
2024-12-30
DOI
https://doi.org/10.13053/cys-28-4-5294
Citations
1
Primary Topic
Personality Traits and Psychology
Type
article
Field-Weighted Citation Impact
0.64
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article

Exploring Personality Traits: A Big Five Profiling of Fictional Movie Characters

Omar Juárez Gambino, Hiram Calvo, Dayana P. Jimenez, Elsy G. Cruz-Murrieta
1 citations
Computación y Sistemas
Personality Traits and Psychology
0.64
article

Exploring Personality Traits: A Big Five Profiling of Fictional Movie Characters

Omar Juárez Gambino, Hiram Calvo, Dayana P. Jimenez, Elsy G. Cruz-Murrieta
article en
1 citations

Abstract

In this article, we explore the viability of establishing a personality profiling system rooted in the Big Five model for movie characters. We curated a corpus sourced from movie scripts and proceeded to evaluate several traditional machine learning models alongside an LSTM model. Our findings indicate that traditional machine learning outperforms the LSTM model in this context.

Computación y SistemasVol. 28(4)
Gender equality
Openalex Percentile: Top 24%
Personality Traits and Psychology
0.64
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Exploring Personality Traits: A Big Five Profiling of Fictional Movie Characters — Omar Juárez Gambino, Hiram Calvo, et al. · Computación y Sistemas (2024) | TGRS Research Map | TGRS