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Myers Briggs Personality Prediction using Machine Learning Techniques
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 175 - Number 23 |
| Year of Publication: 2020 |
| Authors: Nishita Vaddem, Pooja Agarwal |
10.5120/ijca2020920764
|
Nishita Vaddem, Pooja Agarwal . Myers Briggs Personality Prediction using Machine Learning Techniques. International Journal of Computer Applications. 175, 23 ( Oct 2020), 41-44. DOI=10.5120/ijca2020920764
Abstract
In natural language processing and in the scientific realm of psychology, automatic personality analysis from social media is gaining growing interest. Currently, the Myers Briggs Type Indicator (MBTI) is deemed to be one of the most regularly used and reliable forms of personality recognition. The dataset used in this research is derived from Myers Briggs Forum on personalitycafe.com, a medium hitherto ignored for prediction of personality. This dataset is named as Myers-Briggs Type Indicators (MBTI) Personality Type and is available on Kaggle. The aim of this work is to predict the personality type of an individual linked to their posts and to explore the relevance of the test in the study and categorization of human behavior using Learning models.
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