# Personality Type Based on Myers-Briggs Type Indicator with Text Posting Style by using Traditional and Deep Learning

arXiv: https://arxiv.org/abs/2201.08717 · HTML: https://mlsanity.com/paper/2201.08717/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 43 references that are in the map.
- First posted on arXiv 21 Jan 2022.

## Builds on (most cited first, 3 of 3)

- [A Critical Review of Recurrent Neural Networks for Sequence Learning](https://mlsanity.com/paper/1506.00019/) (2015)
- [Computational Sociolinguistics: A Survey](https://mlsanity.com/paper/1508.07544/) (2015)
- [Stacked Bidirectional and Unidirectional LSTM Recurrent Neural Network for Forecasting Network-wide Traffic State with Missing Values](https://mlsanity.com/paper/2005.11627/) (2020)

## Built on by (most cited first, 1 of 1)

- [Behavioral Inference at Scale: The Fundamental Asymmetry Between Motivations and Belief Systems](https://mlsanity.com/paper/2509.05624/) (2025)

## Abstract (arXiv)

The term personality may be expressed in terms of the individual differences in characteristics pattern of thinking, feeling, and behavior. This work presents several machine learning techniques including Naive Bayes, Support Vector Machines, and Recurrent Neural Networks to predict people personality from text based on Myers-Briggs Type Indicator (MBTI). Furthermore, this project applies CRISP-DM, which stands for Cross-Industry Standard Process for Data Mining, to guide the learning process. Since, CRISP-DM is kind of iterative development, we have adopted it with agile methodology, which is a rapid iterative software development method, in order to reduce the development cycle to be minimal.