Reconsidering evidence of moral contagion in online social networks

Jason W. Burton (), Nicole Cruz and Ulrike Hahn
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Jason W. Burton: Birkbeck, University of London
Nicole Cruz: University of New South Wales
Ulrike Hahn: Birkbeck, University of London

Nature Human Behaviour, 2021, vol. 5, issue 12, 1629-1635

Abstract: Abstract The ubiquity of social media use and the digital data traces it produces has triggered a potential methodological shift in the psychological sciences away from traditional, laboratory-based experimentation. The hope is that, by using computational social science methods to analyse large-scale observational data from social media, human behaviour can be studied with greater statistical power and ecological validity. However, current standards of null hypothesis significance testing and correlational statistics seem ill-suited to markedly noisy, high-dimensional social media datasets. We explore this point by probing the moral contagion phenomenon, whereby the use of moral-emotional language increases the probability of message spread. Through out-of-sample prediction, model comparisons and specification curve analyses, we find that the moral contagion model performs no better than an implausible XYZ contagion model. This highlights the risks of using purely correlational evidence from large observational datasets and sounds a cautionary note for psychology’s merge with big data.

Date: 2021
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DOI: 10.1038/s41562-021-01133-5

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