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A robust data-driven approach identifies four personality types across four large data sets

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Listed:
  • Martin Gerlach

    (Northwestern University)

  • Beatrice Farb

    (Northwestern University)

  • William Revelle

    (Northwestern University)

  • Luís A. Nunes Amaral

    (Northwestern University
    Northwestern University
    Northwestern University
    Northwestern University)

Abstract

Understanding human personality has been a focus for philosophers and scientists for millennia1. It is now widely accepted that there are about five major personality domains that describe the personality profile of an individual2,3. In contrast to personality traits, the existence of personality types remains extremely controversial4. Despite the various purported personality types described in the literature, small sample sizes and the lack of reproducibility across data sets and methods have led to inconclusive results about personality types5,6. Here we develop an alternative approach to the identification of personality types, which we apply to four large data sets comprising more than 1.5 million participants. We find robust evidence for at least four distinct personality types, extending and refining previously suggested typologies. We show that these types appear as a small subset of a much more numerous set of spurious solutions in typical clustering approaches, highlighting principal limitations in the blind application of unsupervised machine learning methods to the analysis of big data.

Suggested Citation

  • Martin Gerlach & Beatrice Farb & William Revelle & Luís A. Nunes Amaral, 2018. "A robust data-driven approach identifies four personality types across four large data sets," Nature Human Behaviour, Nature, vol. 2(10), pages 735-742, October.
    • Handle: RePEc:nat:nathum:v:2:y:2018:i:10:d:10.1038_s41562-018-0419-z
    DOI: 10.1038/s41562-018-0419-z
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    Citations

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    Cited by:

    1. Petrik Runst & Jörg Thomä, 2022. "Does personality matter? Small business owners and modes of innovation," Small Business Economics, Springer, vol. 58(4), pages 2235-2260, April.
    2. Xuechen Leng & Jinfeng Han & Yingcan Zheng & Xiaoyong Hu & Hong Chen, 2021. "The Role of a “Happy Personality” in the Relationship of Subjective Social Status and Domain-Specific Satisfaction in China," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 16(4), pages 1733-1751, August.
    3. Katharina Pflügner & Christian Maier & Jens Mattke & Tim Weitzel, 2021. "Personality Profiles that Put Users at Risk of Perceiving Technostress," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(4), pages 389-402, August.
    4. Petrik Runst & Jörg Thomä, 2023. "Resilient entrepreneurs? — revisiting the relationship between the Big Five and self-employment," Small Business Economics, Springer, vol. 61(1), pages 417-443, June.
    5. Runst, Petrik & Thomä, Jörg, 2022. "Resilient entrepreneurs? Revisiting the relationship between the Big Five and self-employment," ifh Working Papers 34/2022, Volkswirtschaftliches Institut für Mittelstand und Handwerk an der Universität Göttingen (ifh).
    6. Stella Stiliadi, 2024. "Personality and Individual Differences in Leadership Behavior. Α Review," Technium Business and Management, Technium Science, vol. 7(1), pages 49-61.
    7. Yannick V. Markhof, 2020. "Divide to Conquer? Latent Preference Types and Country-level Heterogeneity," CSAE Working Paper Series 2020-05, Centre for the Study of African Economies, University of Oxford.
    8. Renato Frey & Shannon M. Duncan & Elke U. Weber, 2023. "Towards a typology of risk preference: Four risk profiles describe two-thirds of individuals in a large sample of the U.S. population," Journal of Risk and Uncertainty, Springer, vol. 66(1), pages 1-17, February.
    9. Patricio Ramírez-Correa & Elizabeth E. Grandón & Jorge Alfaro-Pérez & Giselle Painén-Aravena, 2019. "Personality Types as Moderators of the Acceptance of Information Technologies in Organizations: A Multi-Group Analysis in PLS-SEM," Sustainability, MDPI, vol. 11(14), pages 1-15, July.

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