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Does Scientific Progress Affect Culture? A Digital Text Analysis

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  • Michela Giorcelli
  • Nicola Lacetera
  • Astrid Marinoni

Abstract

We study the interplay between scientific progress and culture through text analysis on a corpus of about eight million books, with the use of techniques and algorithms from machine learning. We focus on a specific scientific breakthrough, the theory of evolution through natural selection by Charles Darwin, and examine the diffusion of certain key concepts that characterized this theory in the broader cultural discourse and social imaginary. We find that some concepts in Darwin’s theory, such as Evolution, Survival, Natural Selection and Competition diffused in the cultural discourse immediately after the publication of On the Origins of Species. Other concepts such as Selection and Adaptation were already present in the cultural dialogue. Moreover, we document semantic changes for most of these concepts over time. Our findings thus show a complex relation between two key factors of long-term economic growth – science and culture. Considering the evolution of these two factors jointly can offer new insights to the study of the determinants of economic development, and machine learning is a promising tool to explore these relationships.

Suggested Citation

  • Michela Giorcelli & Nicola Lacetera & Astrid Marinoni, 2019. "Does Scientific Progress Affect Culture? A Digital Text Analysis," CESifo Working Paper Series 7499, CESifo.
  • Handle: RePEc:ces:ceswps:_7499
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    References listed on IDEAS

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    1. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
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    5. Ran Abramitzky & Isabelle Sin, 2014. "Book Translations As Idea Flows: The Effects Of The Collapse Of Communism On The Diffusion Of Knowledge," Journal of the European Economic Association, European Economic Association, vol. 12(6), pages 1453-1520, December.
    6. Joel Mokyr, 2016. "A Culture of Growth: The Origins of the Modern Economy," Economics Books, Princeton University Press, edition 1, number 10835.
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    Cited by:

    1. Jay Bhattacharya & Mikko Packalen, 2020. "Stagnation and Scientific Incentives," NBER Working Papers 26752, National Bureau of Economic Research, Inc.

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    More about this item

    Keywords

    science; culture; economic history; text analysis; machine learning;
    All these keywords.

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • N00 - Economic History - - General - - - General
    • O00 - Economic Development, Innovation, Technological Change, and Growth - - General - - - General
    • O39 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Other
    • Z19 - Other Special Topics - - Cultural Economics - - - Other

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