SPADE: A Big Five-Mturk Dataset of Argumentative Speech Enriched with Socio-Demographics for Personality Detection

Elma Kerz, Yu Qiao, Sourabh Zanwar, Daniel Wiechmann


Abstract
In recent years, there has been increasing interest in automatic personality detection based on language. Progress in this area is highly contingent upon the availability of datasets and benchmark corpora. However, publicly available datasets for modeling and predicting personality traits are still scarce. While recent efforts to create such datasets from social media (Twitter, Reddit) are to be applauded, they often do not include continuous and contextualized language use. In this paper, we introduce SPADE, the first dataset with continuous samples of argumentative speech labeled with the Big Five personality traits and enriched with socio-demographic data (age, gender, education level, language background). We provide benchmark models for this dataset to facilitate further research and conduct extensive experiments. Our models leverage 436 (psycho)linguistic features extracted from transcribed speech and speaker-level metainformation with transformers. We conduct feature ablation experiments to investigate which types of features contribute to the prediction of individual personality traits.
Anthology ID:
2022.lrec-1.688
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
6405–6419
Language:
URL:
https://aclanthology.org/2022.lrec-1.688
DOI:
Bibkey:
Cite (ACL):
Elma Kerz, Yu Qiao, Sourabh Zanwar, and Daniel Wiechmann. 2022. SPADE: A Big Five-Mturk Dataset of Argumentative Speech Enriched with Socio-Demographics for Personality Detection. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 6405–6419, Marseille, France. European Language Resources Association.
Cite (Informal):
SPADE: A Big Five-Mturk Dataset of Argumentative Speech Enriched with Socio-Demographics for Personality Detection (Kerz et al., LREC 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.lrec-1.688.pdf
Data
PANDORA