Interesting stories often are built around interesting characters. Finding and detailing what makes an interesting character is a real challenge, but certainly a significant cue is the character personality traits. Our exploratory work tests the adaptability of the current personality traits theories to literal characters, focusing on the analysis of utterances in theatre scripts. And, at the opposite, we try to find significant traits for interesting characters. Our preliminary results demonstrate that our approach is reasonable. Using machine learning for gaining insight into the personality traits of fictional characters can make sense.

Personality traits recognition in literary texts / Pizzolli, Daniele; Strapparava, Carlo. - ELETTRONICO. - (2019), pp. 107-111. ((Intervento presentato al convegno Second Workshop on Storytelling @ACL 2019 tenutosi a Florence, Italy nel August 2019.

Personality traits recognition in literary texts

Carlo Strapparava
2019

Abstract

Interesting stories often are built around interesting characters. Finding and detailing what makes an interesting character is a real challenge, but certainly a significant cue is the character personality traits. Our exploratory work tests the adaptability of the current personality traits theories to literal characters, focusing on the analysis of utterances in theatre scripts. And, at the opposite, we try to find significant traits for interesting characters. Our preliminary results demonstrate that our approach is reasonable. Using machine learning for gaining insight into the personality traits of fictional characters can make sense.
Proceedings of the Second Workshop on Storytelling
USA
Association for Computational Linguistics
978-1-950737-44-4
Pizzolli, Daniele; Strapparava, Carlo
Personality traits recognition in literary texts / Pizzolli, Daniele; Strapparava, Carlo. - ELETTRONICO. - (2019), pp. 107-111. ((Intervento presentato al convegno Second Workshop on Storytelling @ACL 2019 tenutosi a Florence, Italy nel August 2019.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/344018
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