An experimental study to measure the environmental effect on human behavior and emotions using multi-output regression

Abstract

Emotions play a very vital role in human life. Emotions originate in human brain due to biological, neurological and psychological effects and influence our behavior and decision-making. This study explores the effect of environment on human emotions and behavior using questionnaire data and by applying multi-output regression. Situation based script questionnaires have been prepared to collect the responses from the participants. Questionnaires collect the demographic information, Age group, gender, and their current work in the hand at the time of responding the questions.  For every question, participants have to choose one of the suitable emotions classes out of the five classes. After collecting the responses from 95 participants on five emotional classes, analysis has been conducted using three techniques i.e. descriptive analysis, single class using support vector machine and multiple classes using multi regression algorithm. Experiment results of the proposed system achieved 80% accuracy in SVM for a single class. In multi classes, results compare with different classes like emotions class with environment, emotions with age and with demographic data for multi-output regression, random forest and decision tree classifiers. Experimental results show that the proposed system performs well as compared to the entire existing system available in literature.