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Big Data under the Microscope and Brains in Social Context

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  • Matthew Brook O’Donnell
  • Emily B. Falk

Abstract

Methods for analyzing neural and computational social science data are usually used by different types of scientists and generally seen as distinct, but they strongly complement one another. Computational social science methodologies can strengthen and contextualize individual-level analysis, specifically our understanding of the brain. Neuroscience can help to unpack the mechanisms that lead from micro- through meso- to macro-level observations. Integrating levels of analysis is essential to unified progress in social research. We present two example areas that illustrate this integration. First, combining egocentric social network data with neural variables from the “egos†provides insight about why and for whom certain types of antismoking messages may be more or less effective. Second, combining tools from natural language processing with neuroimaging reveals mechanisms involved in successful message propagation, and suggests links from microscopic to macroscopic scales.

Suggested Citation

  • Matthew Brook O’Donnell & Emily B. Falk, 2015. "Big Data under the Microscope and Brains in Social Context," The ANNALS of the American Academy of Political and Social Science, , vol. 659(1), pages 274-289, May.
    • Handle: RePEc:sae:anname:v:659:y:2015:i:1:p:274-289
    DOI: 10.1177/0002716215569446
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    References listed on IDEAS

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    3. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
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