International Journal of Science and Technology (IJST)

Unveiling the Landscape of Happiness Prediction with Machine Learning: A PRISMA-Guided Systematic Review

This state-of-the-art paper includes a detailed systematic literature review using the PRISMA of Prediction Techniques used to predict the happiness of humans or nations. It is said that the most significant aspect of life is Happiness. Machine learning performs well at predicting the happiness index, having achieved success in areas such as weather prediction, image processing, fraud detection, sound prediction, and health care. In this paper, a systematic mapping survey is conducted to predict the happiness index using machine learning techniques, covering the period from 2018 to 2023. This study also includes scales and questionnaires for measuring happiness. Academic works are reviewed that suggest, illustrate, and analyse happiness measurement scales and questionnaires. After compiling a pool of 250 papers and applying a set of inclusion and exclusion criteria, a final pool of 150 relevant papers is obtained. Finally, the review concludes with an overview of the literature on an individual’s happiness from an analytical perspective and discusses the measurement scales and questionnaires used in predictive models. Therefore, the primary purpose of this study is to analyse previous work on predicting happiness and the scales used for prediction.