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Human social sensing is an untapped resource for computational social science

Author

Listed:
  • Mirta Galesic

    (Santa Fe Institute
    Complexity Science Hub Vienna
    Vermont Complex Systems Center, University of Vermont
    University of Potsdam)

  • Wändi Bruine de Bruin

    (University of South California)

  • Jonas Dalege

    (Santa Fe Institute)

  • Scott L. Feld

    (Purdue University)

  • Frauke Kreuter

    (University of Maryland
    Ludwig Maximilians Universität München)

  • Henrik Olsson

    (Santa Fe Institute)

  • Drazen Prelec

    (Sloan School of Management, MIT
    MIT
    MIT)

  • Daniel L. Stein

    (New York University)

  • Tamara van der Does

    (Santa Fe Institute)

Abstract

The ability to ‘sense’ the social environment and thereby to understand the thoughts and actions of others allows humans to fit into their social worlds, communicate and cooperate, and learn from others’ experiences. Here we argue that, through the lens of computational social science, this ability can be used to advance research into human sociality. When strategically selected to represent a specific population of interest, human social sensors can help to describe and predict societal trends. In addition, their reports of how they experience their social worlds can help to build models of social dynamics that are constrained by the empirical reality of human social systems.

Suggested Citation

  • Mirta Galesic & Wändi Bruine de Bruin & Jonas Dalege & Scott L. Feld & Frauke Kreuter & Henrik Olsson & Drazen Prelec & Daniel L. Stein & Tamara van der Does, 2021. "Human social sensing is an untapped resource for computational social science," Nature, Nature, vol. 595(7866), pages 214-222, July.
    • Handle: RePEc:nat:nature:v:595:y:2021:i:7866:d:10.1038_s41586-021-03649-2
    DOI: 10.1038/s41586-021-03649-2
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    Cited by:

    1. You-Hai Lu & Peixue Liu & Xiaowan Zhang & Jun Zhang & Caiyun Shen, 2022. "Spatial-Temporal Differences in the Effect of Epidemic Risk Perception on Potential Travel Intention: A Macropsychology-Based Risk Perception Perspective," SAGE Open, , vol. 12(4), pages 21582440221, December.
    2. Jennifer M. Murray & Sharon C. Sánchez-Franco & Olga L. Sarmiento & Erik O. Kimbrough & Christopher Tate & Shannon C. Montgomery & Rajnish Kumar & Laura Dunne & Abhijit Ramalingam & Erin L. Krupka & F, 2023. "Selection homophily and peer influence for adolescents’ smoking and vaping norms and outcomes in high and middle-income settings," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-35, December.
    3. Isabelle Bonhoure & Anna Cigarini & Julián Vicens & Bàrbara Mitats & Josep Perelló, 2023. "Reformulating computational social science with citizen social science: the case of a community-based mental health care research," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    4. Wei Gao & Xiaoli Sun & Mei Zhao & Yong Gao & Haoran Ding, 2024. "Evaluate Human Perception of the Built Environment in the Metro Station Area," Land, MDPI, vol. 13(1), pages 1-25, January.

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