Personality Traits Recognition in Literary Texts

Daniele Pizzolli, Carlo Strapparava


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. The preliminary results demonstrate that our approach is reasonable. Using machine learning for gaining insight into the personality traits of fictional characters can make sense.
Anthology ID:
W19-3411
Volume:
Proceedings of the Second Workshop on Storytelling
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Francis Ferraro, Ting-Hao ‘Kenneth’ Huang, Stephanie M. Lukin, Margaret Mitchell
Venue:
Story-NLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
107–111
Language:
URL:
https://aclanthology.org/W19-3411
DOI:
10.18653/v1/W19-3411
Bibkey:
Cite (ACL):
Daniele Pizzolli and Carlo Strapparava. 2019. Personality Traits Recognition in Literary Texts. In Proceedings of the Second Workshop on Storytelling, pages 107–111, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Personality Traits Recognition in Literary Texts (Pizzolli & Strapparava, Story-NLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-3411.pdf