Open AccessBig Five Personality Prediction from Social Media Data using Machine Learning Techniques
Author(s) -
Suman Maloji,
Kasiprasad Mannepalli,
N. Sravani,
Kim J,
Choragudi Sasidhar
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.d7946.049420
Subject(s) - machine learning , artificial intelligence , personality , computer science , support vector machine , naive bayes classifier , random forest , big five personality traits , social media , logistic regression , recall , psychology , social psychology , world wide web , cognitive psychology
Personality has been important for a number of types of cooperation; it has useful in predicting job achievement, expert and emotional relationship achievement, and even tendency towards a variety of interfaces. To accurately examine the characters of users, a personality test must be carried out. In numerous areas of online life it is usually impractical to use character research. . We used SVM classification, Random Forest algorithm, Naïve Bayes Algorithm and Logistic regression to comparatively predict the user’s personality accurately. The main goal of the paper is to evaluate the machine learning models using the four parameters- accuracy, precision, recall, f1 score and basing upon these parameters the best machine learning model will be used to classify the big five personality traits of the twitter users.