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Social Learning of Risk for COVID-19 Infection

Research Project

Project/Area Number 21K13276
Research Category

Grant-in-Aid for Early-Career Scientists

Allocation TypeMulti-year Fund
Review Section Basic Section 07040:Economic policy-related
Research InstitutionTohoku University

Principal Investigator

Sato Masahiro  東北大学, 国際文化研究科, 准教授 (60622214)

Project Period (FY) 2021-04-01 – 2025-03-31
Project Status Completed (Fiscal Year 2024)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2023: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2022: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2021: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Keywords社会的学習 / 消費者行動 / リスク / 不確実性 / 市場とのコミュニケーション / 学習 / 政策の不確実性 / イノベーション / ビッグデータ / COVID-19 / 製品安全
Outline of Research at the Start

社会的学習(social learning)とは、他者を観測することや他者との相互作用によって促進される学習を言う。構成員ごとに観測する対象が異なることは、集団における社会的学習の効率を向上させるか?向上させるとしたら、それはどのような条件の下においてか?本研究では、COVID-19の感染リスクに関する認識形成等を例として取り上げ、観測対象やそれに基づく認識の多様性が、社会的学習にどのような影響を与えるかを実証的に明らかにする。

Outline of Final Research Achievements

This study examined how people perceive and learn from information related to risk and uncertainty from various perspectives. A study focusing on mask purchasing behavior during the initial phase of the COVID-19 pandemic revealed that individuals’ past experiences encouraged self-protective behaviors in the early stages of the crisis, while the volume of newly acquired information became a key driver of such behavior in the subsequent period. Furthermore, leveraging the rapid advances in large language models during the research period, another study successfully developed indicators to quantify different types of perceived uncertainty based on the content of newspaper articles discussing public policy.

Academic Significance and Societal Importance of the Research Achievements

リスクや不確実性に関する情報を人々がどのように受容し、学習するのかを明らかにすることで、危機時における政策の改善に活かすことができる。例えば、マスクの購入行動に関する研究からは、科学的知見が十分にない未知の危機時において、政府がどのようなタイミングやチャネルで情報を一般市民に提供すべきかを考えることができる。また、政策の不確実性に関する研究からは、不確実性の種類ごとに適切な市場とのコミュニケーションのあり方を導き出すことができる。

Report

(5 results)
  • 2024 Annual Research Report   Final Research Report ( PDF )
  • 2023 Research-status Report
  • 2022 Research-status Report
  • 2021 Research-status Report
  • Research Products

    (7 results)

All 2025 2024 2021

All Journal Article (4 results) (of which Peer Reviewed: 1 results,  Open Access: 4 results) Presentation (3 results) (of which Int'l Joint Research: 2 results)

  • [Journal Article] A novel content-based approach to measuring monetary policy uncertainty using fine-tuned LLMs2025

    • Author(s)
      Ito Arata、Sato Masahiro、Ota Rui
    • Journal Title

      Finance Research Letters

      Volume: 75 Pages: 106832-106832

    • DOI

      10.1016/j.frl.2025.106832

    • Related Report
      2024 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] GAI: Generative Agents for Innovation2024

    • Author(s)
      Masahiro Sato
    • Journal Title

      arXiv

      Volume: arXiv:2412.18899

    • Related Report
      2024 Annual Research Report
    • Open Access
  • [Journal Article] Content-Based Metric on Monetary Policy Uncertainty by Using Large Language Models2024

    • Author(s)
      Ito Arata、Sato Masahiro、Ota Rui
    • Journal Title

      SSRN

      Volume: 50511287 Pages: 1-17

    • DOI

      10.2139/ssrn.5051287

    • Related Report
      2024 Annual Research Report
    • Open Access
  • [Journal Article] Content-based Metric on Monetary Policy Uncertainty by Using Large Language Models2024

    • Author(s)
      Ito Arata、Sato Masahiro、Ota Rui
    • Journal Title

      RIETI Discussion Paper Series

      Volume: 24-E-080

    • Related Report
      2024 Annual Research Report
    • Open Access
  • [Presentation] Content-based metric on monetary policy uncertainty using large-scale language models2024

    • Author(s)
      Arata Ito, Masahiro Sato, Rui Ota
    • Organizer
      15th International Conference on Management, Economics and Humanities
    • Related Report
      2024 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Dynamic Recycling-point System Using Deep Reinforcement Learning2024

    • Author(s)
      Masahiro Sato
    • Organizer
      15th International Conference on Management, Economics and Humanities
    • Related Report
      2024 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 表流水と地下水の連結利用による安定化機能に対するオープンアクセスの影響について2021

    • Author(s)
      張 澤宇, 佐藤 正弘
    • Organizer
      環境経済・政策学会2021年大会
    • Related Report
      2021 Research-status Report

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Published: 2021-04-28   Modified: 2026-01-16  

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