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Modelling Subjective Attractiveness

Author

Listed:
  • Konrad Lewszyk

    (University of Warsaw, Faculty of Economic Sciences and Data Science Lab WNE UW)

  • Piotr Wójcik

    (University of Warsaw, Faculty of Economic Sciences and Data Science Lab WNE UW)

Abstract

Attractive people obtain greater economic and reproductive success. This article attempts to grasp individual preferences of facial attractiveness and create reliable models that will accurately predict a beauty score on a binary and quintary scale. Based on extensive research conducted on factors of attractiveness, we derive the most important facial features that have the highest impact in beauty perception. Based on a sample of 681 images of faces using facial a landmark detector. We derive various numerical features represented by face characteristics and. The application of various machine learning algorithms shows that attractiveness can be predicted accurately based on facial characteristics. In addition, we show that indeed the attractiveness is subjective as the same features have different importance for different subjects.

Suggested Citation

  • Konrad Lewszyk & Piotr Wójcik, 2023. "Modelling Subjective Attractiveness," Working Papers 2023-06, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2023-06
    as

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    File URL: https://www.wne.uw.edu.pl/download_file/2564/0
    File Function: First version, 2023
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    References listed on IDEAS

    as
    1. Christian Pfeifer, 2012. "Physical attractiveness, employment and earnings," Applied Economics Letters, Taylor & Francis Journals, vol. 19(6), pages 505-510, April.
    2. Douglas W. Yu & Glenn H. Shepard, 1999. "The mystery of female beauty," Nature, Nature, vol. 399(6733), pages 216-216, May.
    3. Michael French, 2002. "Physical appearance and earnings: further evidence," Applied Economics, Taylor & Francis Journals, vol. 34(5), pages 569-572.
    4. Hamermesh, Daniel S. & Meng, Xin & Zhang, Junsen, 2002. "Dress for success--does primping pay?," Labour Economics, Elsevier, vol. 9(3), pages 361-373, July.
    5. John Karl Scholz & Kamil Sicinski, 2015. "Facial Attractiveness and Lifetime Earnings: Evidence from a Cohort Study," The Review of Economics and Statistics, MIT Press, vol. 97(1), pages 14-28, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Attractiveness; beauty-premium; image processing; machine learning; predictive models;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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