International Council for Education, Research and Training

Need of Machine Learning to Predict Happiness: A Systematic Review

Naveen1 and Bhatia, Anupam2

1Research Scholar, DCSA, Chaudhary Ranbir Singh University, Jind, Haryana, India 

2Associate Professor, DCSA, Chaudhary Ranbir Singh University, Jind, Haryana, India


Happiness is a current important subject of study in psychology and social science because it affects people’s day-to-day lives, thoughts and feelings, work habits, and interactions with society and family. There are a number of challenges in Computer Science and Machine Learning to predict happiness index using prediction techniques. This study presents a systematic review using PRISMA style for happiness prediction. During the Literature survey, it was found that many predictive models whether statistical or Machine Learning was designed to predict happiness index but a major emphasis on research remains focused on the factors that are listed in World Happiness Report, i.e., real Gross Domestic Product per capita, social support, healthy life expectancy, freedom to make life choices, generosity and perceptions of corruption. The factor influencing happiness varies due to personal differences, age group and location variation. According to Gallup Poll, the general annual sample for each country is 1,000 people i.e., approximately 0.007% population participated in happiness index measurement. The purpose of this study is to discover and describe new factors related to psychology like stress and emotions, location-based and age group. It is observed that there is a requirement to develop a Machine Learning predictive model which works on psychological factors like mental health, depression, stress, physical well-being, safety, leisure time available and suicidal ideation in addition to economic factors used in World Happiness Index and by targeting a large sample size of populations.

Keywords: Factors Affecting Happiness, Happiness Index, Machine Learning, Prediction Techniques.

Impact Statement

The past researches focus on the accuracy of predictive models which use different Machine Learning approaches to predict Happiness Index. Without knowing the impact of factors on happiness, the existing models are not useful for Phycologist, psychiatrists, Society and any other stakeholders.  New factors that are related to social, psychological, environmental, etc. are never considered in Machine Learning approaches with World Happiness Report. The sample size taken by the World Happiness Report of a country is very small. World Happiness Report is used as a dataset only rather than analysing the factors affecting happiness.

There is a need to develop a Machine Learning model able to analyse maximum factors in a particular situation (geographical, academic, social, psychological, etc.) to predict the Happiness Index of a nation or of a targeted group so that society can be benefited. 

About The Athor

Naveen completed her in Computer Science from Lovely Professional University, Punjab in 2015. She qualified NTA UGC NET examination in 2018. Till now, she has published 5 research papers. Now she is pursuing her PhD under the supervision of Dr Anupam Bhatia from Chaudhary Ranbir Singh University Jind. 

Dr Anupam Bhatia completed his MCA in 2004 and PhD in 2013 from Kurukshetra University, Kurukshetra. He qualified UGC NET examination in December 2005. He did his PhD in the area of Data Mining using Genetic Algorithms. Till now, three research scholars have been awarded PhD under his supervision. Currently, five students are pursuing their PhD under his supervision. In addition to PhD, 7 MPhil and 4 MTech students have also done their dissertations under his supervision. His current research area is Machine Learning and Blockchain Technology. Most of his students research in interdisciplinary areas like Management, Psychology, and Computer Science. Till now he has published 24 research papers and attended 10 Conferences at the National and International Levels as a presenter, and session chair. He had been the Organizing Secretary of One National and One International Conference. He joined as Lecturer at erstwhile Kurukshetra University Post Graduate Regional Centre, Jind on 25th August 2007 as the first teacher of the institution. On 24 th July 2014, as per Chaudhary Ranbir Singh University, Act 2014; KUPGRC, Jind was elevated to Chaudhary Ranbir Singh University, Jind. Since, 25 th August 2021; He is serving as an Associate Professor, at the Department of Computer Science and Applications, Chaudhary Ranbir Singh University, Jind.


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