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Meaningful measures of human society in the twenty-first century

Author

Listed:
  • David Lazer

    (Northeastern University
    Harvard University)

  • Eszter Hargittai

    (University of Zurich)

  • Deen Freelon

    (University of North Carolina at Chapel Hill)

  • Sandra Gonzalez-Bailon

    (University of Pennsylvania)

  • Kevin Munger

    (Pennsylvania State University)

  • Katherine Ognyanova

    (Rutgers University)

  • Jason Radford

    (Northeastern University)

Abstract

Science rarely proceeds beyond what scientists can observe and measure, and sometimes what can be observed proceeds far ahead of scientific understanding. The twenty-first century offers such a moment in the study of human societies. A vastly larger share of behaviours is observed today than would have been imaginable at the close of the twentieth century. Our interpersonal communication, our movements and many of our everyday actions, are all potentially accessible for scientific research; sometimes through purposive instrumentation for scientific objectives (for example, satellite imagery), but far more often these objectives are, literally, an afterthought (for example, Twitter data streams). Here we evaluate the potential of this massive instrumentation—the creation of techniques for the structured representation and quantification—of human behaviour through the lens of scientific measurement and its principles. In particular, we focus on the question of how we extract scientific meaning from data that often were not created for such purposes. These data present conceptual, computational and ethical challenges that require a rejuvenation of our scientific theories to keep up with the rapidly changing social realities and our capacities to capture them. We require, in other words, new approaches to manage, use and analyse data.

Suggested Citation

  • David Lazer & Eszter Hargittai & Deen Freelon & Sandra Gonzalez-Bailon & Kevin Munger & Katherine Ognyanova & Jason Radford, 2021. "Meaningful measures of human society in the twenty-first century," Nature, Nature, vol. 595(7866), pages 189-196, July.
  • Handle: RePEc:nat:nature:v:595:y:2021:i:7866:d:10.1038_s41586-021-03660-7
    DOI: 10.1038/s41586-021-03660-7
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    Cited by:

    1. Li, Tong & Chen, Hui & Liu, Wei & Yu, Guang & Yu, Yongtian, 2023. "Understanding the role of social media sentiment in identifying irrational herding behavior in the stock market," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 163-179.
    2. Bauer, Johannes M., 2022. "Toward new guardrails for the information society," Telecommunications Policy, Elsevier, vol. 46(5).
    3. Simon Willcock & Javier Martinez-Lopez & Norman Dandy & James M. Bullock, 2021. "High Spatial-Temporal Resolution Data across Large Scales Are Needed to Transform Our Understanding of Ecosystem Services," Land, MDPI, vol. 10(7), pages 1-6, July.
    4. Brian Ball & Alexandros Koliousis & Amil Mohanan & Mike Peacey, 2024. "Computational philosophy: reflections on the PolyGraphs project," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-9, December.

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