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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. Svizzero, Serge & Tisdell, Clement, 2019. "Barter and the Origin of Money and Some Insights from the Ancient Palatial Economies of Mesopotamia and Egypt," Economic Theory, Applications and Issues Working Papers 291788, University of Queensland, School of Economics.
    2. 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.
    3. 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.
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