Prajwal Kaushal; Nithin Bharadwaj B P; Pranav M S; Koushik S; Anjan K Koundinya

Myers-briggs Personality Prediction and Sentiment Analysis of Twitter using Machine Learning Classifiers and BERT

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Author(s)

Prajwal Kaushal ^1,* Nithin Bharadwaj B P ¹ Pranav M S ¹ Koushik S ¹ Anjan K Koundinya ¹

1. Department of Computer Science and Engineering, BMS Institute of Technology and Management, Bengaluru, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2021.06.04

Received: 14 Jul. 2021 / Revised: 16 Aug. 2021 / Accepted: 9 Oct. 2021 / Published: 8 Dec. 2021

Index Terms

BERT, MBTI, Machine Learning, Personality Prediction, Sentiment Analysis

Abstract

Twitter being one of the most sophisticated social networking platforms whose users base is growing exponentially, terabytes of data is being generated every day. Technology Giants invest billions of dollars in drawing insights from these tweets. The huge amount of data is still going underutilized. The main of this paper is to solve two tasks. Firstly, to build a sentiment analysis model using BERT (Bidirectional Encoder Representations from Transformers) which analyses the tweets and predicts the sentiments of the users. Secondly to build a personality prediction model using various machine learning classifiers under the umbrella of Myers-Briggs Personality Type Indicator. MBTI is one of the most widely used psychological instruments in the world. Using this we intend to predict the traits and qualities of people based on their posts and interactions in Twitter. The model succeeds to predict the personality traits and qualities on twitter users. We intend to use the analyzed results in various applications like market research, recruitment, psychological tests, consulting, etc, in future.

Cite This Paper

Prajwal Kaushal, Nithin Bharadwaj B P, Pranav M S, Koushik S, Anjan K Koundinya, "Myers-briggs Personality Prediction and Sentiment Analysis of Twitter using Machine Learning Classifiers and BERT", International Journal of Information Technology and Computer Science(IJITCS), Vol.13, No.6, pp.48-60, 2021. DOI:10.5815/ijitcs.2021.06.04

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International Journal of Information Technology and Computer Science (IJITCS)