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Using supervised machine learning to scale human‐coded data: A method and dataset in the board leadership context

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Listed:
  • Harrison, Joseph S.
  • Josefy, Matthew A.
  • Kalm, Matias

    (Tilburg University, School of Economics and Management)

  • Krause, Ryan

Abstract

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Suggested Citation

  • Harrison, Joseph S. & Josefy, Matthew A. & Kalm, Matias & Krause, Ryan, 2022. "Using supervised machine learning to scale human‐coded data: A method and dataset in the board leadership context," Other publications TiSEM abc9f83d-960e-40c5-ae40-3, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:abc9f83d-960e-40c5-ae40-3845302531de
    as

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    File URL: https://repository.tilburguniversity.edu/bitstreams/f6240e5a-db00-4b0c-b0e1-b7d0a96a28d5/download
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    References listed on IDEAS

    as
    1. Matthew Gentzkow & Bryan Kelly & Matt Taddy, 2019. "Text as Data," Journal of Economic Literature, American Economic Association, vol. 57(3), pages 535-574, September.
    2. Kris Boudt & James Thewissen, 2019. "Jockeying for Position in CEO Letters: Impression Management and Sentiment Analytics," Financial Management, Financial Management Association International, vol. 48(1), pages 77-115, March.
    3. Matthew Gentzkow & Bryan T. Kelly & Matt Taddy, 2017. "Text as Data," NBER Working Papers 23276, National Bureau of Economic Research, Inc.
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