# Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality

arXiv: https://arxiv.org/abs/2011.07009 · HTML: https://mlsanity.com/paper/2011.07009/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Nov 2020.

## Built on by (most cited first, 2 of 2)

- [On Text-based Personality Computing: Challenges and Future Directions](https://mlsanity.com/paper/2212.06711/) (2022)
- [Extending the Abstraction of Personality Types based on MBTI with Machine Learning and Natural Language Processing](https://mlsanity.com/paper/2105.11798/) (2021)

## Abstract (arXiv)

As a contribution to personality detection in languages other than English, we rely on distant supervision to create Personal-ITY, a novel corpus of YouTube comments in Italian, where authors are labelled with personality traits. The traits are derived from one of the mainstream personality theories in psychology research, named MBTI. Using personality prediction experiments, we (i) study the task of personality prediction in itself on our corpus as well as on TwiSty, a Twitter dataset also annotated with MBTI labels; (ii) carry out an extensive, in-depth analysis of the features used by the classifier, and view them specifically under the light of the original theory that we used to create the corpus in the first place. We observe that no single model is best at personality detection, and that while some traits are easier than others to detect, and also to match back to theory, for other, less frequent traits the picture is much more blurred.