Abstract
Automatic detection of the Myers-Briggs Type Indicator (MBTI) from short posts attracted noticeable attention in the last few years. Recent studies showed that this is quite a difficult task, especially on commonly used Twitter data. Obtaining MBTI labels is also difficult, as human annotation requires trained psychologists, and automatic way of obtaining them is through long questionnaires of questionable usability for the task. In this paper, we present a method for collecting reliable MBTI labels via only four carefully selected questions that can be applied to any type of textual data.- Anthology ID:
- 2021.ranlp-1.152
- Volume:
- Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
- Month:
- September
- Year:
- 2021
- Address:
- Held Online
- Editors:
- Ruslan Mitkov, Galia Angelova
- Venue:
- RANLP
- SIG:
- Publisher:
- INCOMA Ltd.
- Note:
- Pages:
- 1360–1368
- Language:
- URL:
- https://aclanthology.org/2021.ranlp-1.152
- DOI:
- Cite (ACL):
- Sanja Stajner and Seren Yenikent. 2021. How to Obtain Reliable Labels for MBTI Classification from Texts?. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), pages 1360–1368, Held Online. INCOMA Ltd..
- Cite (Informal):
- How to Obtain Reliable Labels for MBTI Classification from Texts? (Stajner & Yenikent, RANLP 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2021.ranlp-1.152.pdf