A Real Data-Driven Analytical Model to Predict Happiness

A Real Data-Driven Analytical Model to Predict Happiness | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Real Data-Driven Analytical Model to Predict Happiness Aditya Chakraborty, Chris P. Tsokos This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-224834/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose : Philosophers and many modern-day researchers are convinced by the fact that the pursuit of happiness is the ultimate goal for humankind. Aristotle believed that the utmost goal of human life was eudaimonia (interpreted as “happiness,” “human flourishing,” or “a good life.”). Recently, many economists and physiologists have been doing applied research in the areas of subjective well-being (SWB) or happiness and trying to understand how it improves the quality of life of individual beings. Thus, searching for a data-driven analytical model is crucial to predict SWB and enhance the quality of life Methods : Our present study utilizes the world happiness database obtained from the Gallup World Poll on the happiness of 156 countries. However, our study focuses on using only the data of fifty-four developed countries, based on the human development index (HDI). We have developed a non-linear analytical model that predicts the average happiness score based on eleven risk factors with a high degree of accuracy. We also compared our analytical model with three other statistical models, and our model outperformed the rest of the three in terms of RMSE and MAE. Results : Our analytical model includes five important findings. The response of the proposed model is the average score of happiness of individuals in developed countries. In addition to predicting the happiness score, our model identifies the individual risk factors and their corre-sponding interactions that significantly contribute to happiness. We rank these risk factors by their percentage of contributions to the happiness score. We also proceed to rank the developed countries with respect to their predicted happiness score from our developed model. From our study, we found Finland being number one, followed by Denmark. The U.S is fifth and Romania being 54th. Conclusion : The proposed model offers other useful information on the subject area. Our ana-lytical model has been validated and tested to be of high quality, and our prediction of happiness is with a high degree of accuracy. We created a survey questionnaire (appendix 1) based on the data that can be used along with our model by any company for the strategic planning or decision making. Social Policy Applied Statistics International Economics Gallup world poll Subjective well being (SWB) Nonlinear statistical modelling Machine learning regularization techniques Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Full Text Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the latest manuscript can be downloaded and accessed as a PDF. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-224834","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":11018096,"identity":"92e3fa54-f153-4635-873e-8463fd8ad2e9","order_by":0,"name":"Aditya Chakraborty","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYFCCxAYQmcDAAyQ/MDDwAykDQloaG2BaGGcwMEg2ENaSwAjXwsxDjBb+9uT2xzw1dnn8PWcffrZtq5NgYG/eJoFPi8SZh43NPMeSiyXOthtL57YdlmDgOVaGVwvDjUSgFrYDiQ3n2RiAWg7UMUjkmOHVIg/W8u9A4vzzbMy/LUEOk3+DX4sBSAtv24HEDWfb2KQZ25glGCR48GsxBPpl5ty+5MSNZ46xWfacOyzBxpNWbIFPi9zx9Acf3nyzS5x3Jo35xo+yOgl+9sMbb+DTAgJMPMg8NkLKQYDxBzGqRsEoGAWjYOQCANKJTA7pc9VeAAAAAElFTkSuQmCC","orcid":"","institution":"University of South Florida","correspondingAuthor":true,"prefix":"","firstName":"Aditya","middleName":"","lastName":"Chakraborty","suffix":""},{"id":11018097,"identity":"e127aa88-cba3-4ca5-b57d-ca5310ed58ee","order_by":1,"name":"Chris P. 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Aristotle believed that the utmost goal of human life was eudaimonia (interpreted as “happiness,” “human flourishing,” or “a good life.”). Recently, many economists and physiologists have been doing applied research in the areas of subjective well-being (SWB) or happiness and trying to understand how it improves the quality of life of individual beings. Thus, searching for a data-driven analytical model is crucial to predict SWB and enhance the quality of life\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Our present study utilizes the world happiness database obtained from the Gallup World Poll on the happiness of 156 countries. However, our study focuses on using only the data of fifty-four developed countries, based on the human development index (HDI). We have developed a non-linear analytical model that predicts the average happiness score based on eleven risk factors with a high degree of accuracy. 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