Abstract
This study conducted an in-depth analysis of the factors influencing the happiness of Koreans by utilizing SHAP (SHapley Additive exPlanations), a machine learning-based XAI (eXplainable Artificial Intelligence) technique. We examined various variables -including job satisfaction, family life satisfaction, health satisfaction, and environmental satisfaction- to identify both linear and nonlinear relationships affecting happiness within complex contexts. Notably, the findings reveal that feelings of alienation experienced during SNS (Social Network Service) use negatively impact happiness, and that interpersonal trust is a key factor in mitigating this adverse effect. By performing individual-level predictions, we confirmed that the influence of the same variables on happiness can vary based on individual characteristics and contexts. These results suggest that policy efforts are needed to alleviate feelings of alienation from SNS use and to enhance interpersonal trust to improve personal happiness. The significance of this study lies in its precise and detailed discussion of the factors affecting the happiness of Koreans through machine learning.
Published Version
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