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Battling the coronavirus ‘infodemic’ among social media users in Kenya and Nigeria

Abstract

How can we induce social media users to be discerning when sharing information during a pandemic? An experiment on Facebook Messenger with users from Kenya (n = 7,498) and Nigeria (n = 7,794) tested interventions designed to decrease intentions to share COVID-19 misinformation without decreasing intentions to share factual posts. The initial stage of the study incorporated: (1) a factorial design with 40 intervention combinations; and (2) a contextual adaptive design, increasing the probability of assignment to treatments that worked better for previous subjects with similar characteristics. The second stage evaluated the best-performing treatments and a targeted treatment assignment policy estimated from the data. We precisely estimate null effects from warning flags and related article suggestions, tactics used by social media platforms. However, nudges to consider the accuracy of information reduced misinformation sharing relative to control by 4.9% (estimate = −2.3 percentage points, 95% CI = [−4.2, −0.35]). Such low-cost scalable interventions may improve the quality of information circulating online.

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Fig. 1: Learning stage estimates.
Fig. 2: Response estimates.
Fig. 3: Selected covariate means by restricted targeted policy assignment.
Fig. 4: Headline- and respondent-level treatments tested in the evaluation stage.

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Data availability

The data that support the findings of this study are available at https://github.com/gsbDBI/infodemic-replication. Source data are provided with this paper.

Code availability

The analysis code that generate the figures, tables and results presented in this study are available at https://github.com/gsbDBI/infodemic-replication.

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Acknowledgements

We received advertising credits for this study from Facebook Health and funding from the Golub Capital Social Impact Lab and Office of Naval Research grant no. N00014-19-1-246 (S.A.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. For exceptional research assistance, we thank Z. (J.) Li, R. Ruiz, U. Byambadalai and H. (T.) Zong. We thank J. Davis, S. Grossman, L. Jakli, E. Jee, T. Kumar, E. Palikot and A. Siegel for feedback and comments, as well as the participants of the seminar series of the Development Innovation Lab at the Becker Friedman Institute. We thank J. Kiselik for editorial assistance.

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M.O.W., L.R. and S.A. designed the research and wrote the paper. M.O.W. and L.R. performed the experimental studies. M.O.W. analysed the data, with input from S.A. and L.R.

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Correspondence to Molly Offer-Westort.

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Nature Human Behaviour thanks Gordon Pennycook, Xiao Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Information

Supplementary Figs. 1–5 and Tables 1–13. Supplementary methods materials are presented in Section S1. Supplementary results are presented in Section S2.

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Source Data Fig. 1

Discernment measure mean response estimates, standard errors and probabilities for learning stage.

Source Data Fig. 2

Discernment and other sharing measure mean response estimates, standard errors, for evaluation stage.

Source Data Fig. 3

Covariate means, standard errors by assignment group in evaluation stage.

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Offer-Westort, M., Rosenzweig, L.R. & Athey, S. Battling the coronavirus ‘infodemic’ among social media users in Kenya and Nigeria. Nat Hum Behav (2024). https://doi.org/10.1038/s41562-023-01810-7

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