Abstract
This paper introduces a novel textual dataset comprising fictional characters’ lines with annotations based on their gender and Big-Five personality traits. Using psycholinguistic findings, we compared texts attributed to fictional characters and real people with respect to their genders and personality traits. Our results indicate that imagined personae mirror most of the language categories observed in real people while demonstrating them in a more expressive manner.- Anthology ID:
- 2024.cogalex-1.13
- Volume:
- Proceedings of the Workshop on Cognitive Aspects of the Lexicon @ LREC-COLING 2024
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Michael Zock, Emmanuele Chersoni, Yu-Yin Hsu, Simon de Deyne
- Venue:
- CogALex
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 114–119
- Language:
- URL:
- https://aclanthology.org/2024.cogalex-1.13
- DOI:
- Cite (ACL):
- Marina Tiuleneva, Vadim A. Porvatov, and Carlo Strapparava. 2024. Big-Five Backstage: A Dramatic Dataset for Characters Personality Traits & Gender Analysis. In Proceedings of the Workshop on Cognitive Aspects of the Lexicon @ LREC-COLING 2024, pages 114–119, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Big-Five Backstage: A Dramatic Dataset for Characters Personality Traits & Gender Analysis (Tiuleneva et al., CogALex 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.cogalex-1.13.pdf