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Prediction of Prefecture-Level Subjective Well-Being in Japan by Using Google Trends and Socioeconomic Data: Machine Learning Model Development and Validation Study
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Predicting Prefectural Subjective Well-Being in Japan Using Google Trends and Socioeconomic Data: An Infodemiology-Informed Stacked-Ensemble Study
Kenichi Kishi;
Hisashi Hayashi;
Shigeomi Koshimizu
ABSTRACT
Using 2022-2025 data for Japan’s 47 prefectures, we test whether Google Trends indicators improves stacked-ensemble predictions of prefectural subjective well-being.
Citation
Please cite as:
Kishi K, Hayashi H, Koshimizu S
Prediction of Prefecture-Level Subjective Well-Being in Japan by Using Google Trends and Socioeconomic Data: Machine Learning Model Development and Validation Study