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Prediction of Prefecture-Level Subjective Well-Being in Japan by Using Google Trends and Socioeconomic Data: Machine
Kenichi Kishi1, Hisashi Hayashi1, Shigeomi Koshimizu1
1Advanced Institute of Industrial Technology, Tokyo, Japan.
JMIR Formative Research
|March 20, 2026
Abstract:
Incorporating prespecified Google Trends indicators into leakage-controlled stacked-ensemble models improved a 2025 holdout prediction of subjective well-being by using 2022-2025 data from Japan's 47 prefectures, reducing the mean squared error from 0.0050 to 0.0045.
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