Personality recognition from text based on the MBTI model

• Main Author: Chew, Andrel Kit Waye
• Other Authors: Erik Cambria
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/156130
• Institution: Nanyang Technological University

Personality is the driving factor for human behavior. Distinguished thought patterns, emotionality, and temperament are some aspects that can be understood from a personality. One such method of predicting personality is through the Myers-Briggs Type Indicator (MBTI) personality model, represented by four-character dichotomies. Through traditional means, one's personality is obtainable through questionnaires and surveys. However, due to the nature of such self-assessments, biased outcomes are produced. For instance, job applicants may provide the company with fabricated answers in personality tests, which breaches the integrity of the assessment results. Consequently, the ambiguity of results will be leading to misrepresentation and unreliability of information. The motivation of this project is to automate the process of personality prediction based on the MBTI personality model. With the unveiling of more state-of-the-art technologies in Natural Language Processing (NLP), the project has demonstrated a broad spectrum of deep learning approaches. These approaches include experiments in neural networks with word embeddings, transformers, and multi-task learning. In addition, an MBTI prediction tool was implemented for the ease of personality prediction as an alternative to the surveys and questionnaires.