Research Article Open Access

Analyze and Predict the 2022 World Happiness Report Based on the Past Year's Dataset

Yifei Zhang1
  • 1 School of Physical Science, University of Liverpool, United Kingdom

Abstract

Through the impact of the COVID-19, people around the world have been affected to various degrees. Thus, it is more interesting to compare the happiness reported between 2022/2021 and before 2019. This article concludes 5 years of happiness scores data including family, Gross Domestic Product (GDP), health, freedom, generosity trust, and dystopia residual. Happiness scores are considered appropriate indicators to measure the progress of social development. This study presents two linear regression models to predict happiness scores across countries in 2022. Data is sourced from the world happiness report dataset from 2015-2021, available in open source. Preliminary exploratory data analysis was carried out to select the most appropriate variables to include in the models. The models’ accuracy was tested by comparing the output values to the true 2022 world happiness report data. The experiment results show that the linear regression achieved a Root Mean Square Error (RMSE) = 0.236 and Mean Squared Error (MSE) = 0.056 for 2022.

Journal of Computer Science
Volume 19 No. 4, 2023, 483-492

DOI: https://doi.org/10.3844/jcssp.2023.483.492

Submitted On: 20 September 2022 Published On: 16 March 2023

How to Cite: Zhang, Y. (2023). Analyze and Predict the 2022 World Happiness Report Based on the Past Year's Dataset. Journal of Computer Science, 19(4), 483-492. https://doi.org/10.3844/jcssp.2023.483.492

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Keywords

  • World Happiness Report
  • Linear Regression
  • Data Analysis
  • Machine Learning