Computational linguistic lens into gendered actions in film. (IMAGE)

PLOS

Computational linguistic lens into gendered actions in film.

Caption

The researches started with the annotation process, where they collected manual annotations for 9,613 descriptions and over 1.5 million gender expression labels for characters. Then they developed a machine learning model to identify actions, agents and patients from the natural language found in the movie scripts. In the final step, they undertook statistical analysis to uncover portrayal differences along characters’ portrayed attributes.

Credit

Martinez et al., 2022, PLOS ONE, CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)

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Credit must be given to the creator.

License

CC BY

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