Personality detection from text, based on the MBTI model

Personality is a person's distinguishing set of behaviours, ways of perception and emotional patters. It also plays a key role in everyday life, and the addition of personality awareness across various fields may be of great benefit. The idea of obtaining a person's personality type withou...

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Main Author: Christienne Grace Regodon, Visco
Other Authors: Erik Cambria
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/140960
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1409602020-06-03T03:59:21Z Personality detection from text, based on the MBTI model Christienne Grace Regodon, Visco Erik Cambria School of Computer Science and Engineering cambria@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Document and text processing Personality is a person's distinguishing set of behaviours, ways of perception and emotional patters. It also plays a key role in everyday life, and the addition of personality awareness across various fields may be of great benefit. The idea of obtaining a person's personality type without having to go through lengthy and at times biased traditional methods of questionnaires and interviews is thus of interest. With the growing popularity of online social networking sites, it is no longer difficult to get a hold of text generated by users of the various platforms. And with the advances in Artificial Intelligence (AI), it is now possible to make use of machine learning algorithms to detect personality. In this project, personality detection based on the Myers–Briggs Type Indicator (MBTI) personality model is explored using various machine learning algorithms. Data is first pre-processed and prepared to train the various machine learning algorithms that will form the classification models. The performance of each model is then recorded by testing them against data that has not been used for training the models. The model that performed the best can thus be evaluated and improvements can be made upon the model to increase accuracy in future work. Bachelor of Engineering (Computer Science) 2020-06-03T03:59:21Z 2020-06-03T03:59:21Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/140960 en SCSE19-0421 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Computer science and engineering::Computing methodologies::Document and text processing
spellingShingle Engineering::Computer science and engineering::Computing methodologies::Document and text processing
Christienne Grace Regodon, Visco
Personality detection from text, based on the MBTI model
description Personality is a person's distinguishing set of behaviours, ways of perception and emotional patters. It also plays a key role in everyday life, and the addition of personality awareness across various fields may be of great benefit. The idea of obtaining a person's personality type without having to go through lengthy and at times biased traditional methods of questionnaires and interviews is thus of interest. With the growing popularity of online social networking sites, it is no longer difficult to get a hold of text generated by users of the various platforms. And with the advances in Artificial Intelligence (AI), it is now possible to make use of machine learning algorithms to detect personality. In this project, personality detection based on the Myers–Briggs Type Indicator (MBTI) personality model is explored using various machine learning algorithms. Data is first pre-processed and prepared to train the various machine learning algorithms that will form the classification models. The performance of each model is then recorded by testing them against data that has not been used for training the models. The model that performed the best can thus be evaluated and improvements can be made upon the model to increase accuracy in future work.
author2 Erik Cambria
author_facet Erik Cambria
Christienne Grace Regodon, Visco
format Final Year Project
author Christienne Grace Regodon, Visco
author_sort Christienne Grace Regodon, Visco
title Personality detection from text, based on the MBTI model
title_short Personality detection from text, based on the MBTI model
title_full Personality detection from text, based on the MBTI model
title_fullStr Personality detection from text, based on the MBTI model
title_full_unstemmed Personality detection from text, based on the MBTI model
title_sort personality detection from text, based on the mbti model
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/140960
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