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Currently accepted at: JMIR Formative Research

Date Submitted: Nov 30, 2025
Open Peer Review Period: Dec 9, 2025 - Feb 3, 2026
Date Accepted: Mar 6, 2026
(closed for review but you can still tweet)

This paper has been accepted and is currently in production.

It will appear shortly on 10.2196/88696

The final accepted version (not copyedited yet) is in this tab.

Prediction of Prefecture-Level Subjective Well-Being in Japan Using Google Trends and Socioeconomic Data: Machine Learning Model Development and Validation Study

  • Kenichi Kishi; 
  • Hisashi Hayashi; 
  • Shigeomi Koshimizu

ABSTRACT

Using 2022–2025 data from Japan’s 47 prefectures, we test whether adding 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 Using Google Trends and Socioeconomic Data: Machine Learning Model Development and Validation Study

JMIR Formative Research. 06/03/2026:88696 (forthcoming/in press)

DOI: 10.2196/88696

URL: https://preprints.jmir.org/preprint/88696

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