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Feature Engineering for Quantitative Analysis of Cultural Evolution

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  • Celli, Fabio

Abstract

In this paper we introduce the use of time-resolved variables to represent the evolution of categorical variables through time. Traditionally, the presence or absence of categorical variables are treated as 1 or 0 for computational purposes, and then aggregated with compression techniques, potentially generating biases when the information compressed into different variables is uneven. Our tests reveal that the use of time-resolved variables can help to prevent these biases, to assure higher reliability of the results and to allow an easier explanation of the models.

Suggested Citation

  • Celli, Fabio, 2022. "Feature Engineering for Quantitative Analysis of Cultural Evolution," SocArXiv aj8xk, Center for Open Science.
    • Handle: RePEc:osf:socarx:aj8xk
    DOI: 10.31219/osf.io/aj8xk
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    References listed on IDEAS

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    1. Serge Svizzero & Clement Tisdell, 2019. "Barter and the Origin of Money and Some Insights from the Ancient Palatial Economies of Mesopotamia and Egypt," Working Papers hal-02274856, HAL.
    2. Qiongjie Kou & Quanyou Zhang & Laiqun Xu & Yaohui Li & Yong Feng & Huiting Wei, 2022. "Mobile Learning Strategy Based on Principal Component Analysis," International Journal of Information Systems in the Service Sector (IJISSS), IGI Global, vol. 14(3), pages 1-12, July.
    3. Gregory K. Dow & Clyde G. Reed & Simon Woodcock, 2016. "The Economics Of Exogamous Marriage In Small-Scale Societies," Economic Inquiry, Western Economic Association International, vol. 54(4), pages 1805-1823, October.
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