Why Is MBTI Personality Detection from Texts a Difficult Task?

Sanja Stajner, Seren Yenikent


Abstract
Automatic detection of the four MBTI personality dimensions from texts has recently attracted noticeable attention from the natural language processing and computational linguistic communities. Despite the large collections of Twitter data for training, the best systems rarely even outperform the majority-class baseline. In this paper, we discuss the theoretical reasons for such low results and present the insights from an annotation study that further shed the light on this issue.
Anthology ID:
2021.eacl-main.312
Volume:
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Month:
April
Year:
2021
Address:
Online
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3580–3589
Language:
URL:
https://aclanthology.org/2021.eacl-main.312
DOI:
10.18653/v1/2021.eacl-main.312
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.eacl-main.312.pdf