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The heterogeneous effects of social support on the adoption of Facebook’s vaccine profile frames feature

Author

Listed:
  • Nadav Rakocz

    (University of California Los Angeles (UCLA))

  • Sindhu Ernala

    (Core Data Science, Meta Platforms)

  • Israel Nir

    (Core Data Science, Meta Platforms)

  • Udi Weinsberg

    (Core Data Science, Meta Platforms)

  • Amit Bahl

    (Core Data Science, Meta Platforms)

Abstract

Achieving widespread COVID-19 vaccine acceptance is a key step to global recovery from the pandemic, but hesitancy towards vaccination remains a major challenge. Social proof, where a person’s attitude towards vaccination is influenced by their belief in the attitudes of their social network, has been shown to be effective for making in-roads upon hesitancy. However, it is not easy to know the attitudes of one’s network, nor reliably signal one’s own feelings towards COVID-19 vaccines, minimizing the impact of the social influence channel. To address this issue, Facebook launched a feature that enables users to overlay a message indicating that they support vaccination upon their profile picture. To raise awareness of these vaccine profile frames (VPFs), users received a variety of promotional messages from Facebook, a subset of which contained the social context of friends who had already adopted the frame. Leveraging this variation in promotional messaging, we analyzed the adoption pattern of VPFs in the US to determine the most effective strategies to drive VPF usage. We found that adoption is driven by a pattern of complex diffusion, where multiple exposures to the adoption decisions of others increased VPF uptake, and that there is substantial heterogeneity in the adoption response associated with prior vaccine beliefs, whether the promotion had a social component and closeness of the tie included in social promotions. Specifically, we observed resistance to adoption correlated with an aversion to follow authoritative health pages and stronger adoption effects from social promotions containing close friends. We also confirmed this finding of the value of strong ties through a randomized field experiment and heterogeneous treatment effects modeling. In contrast to studies that have shown the importance of less close relationships in vaccine decision-making, we found little effect from awareness of VPF adoption by weak ties. Finally, we detected no significant backfire effect for expressing support for COVID-19 vaccines via VPFs. Together, these results suggest that social proof provided by close friends may be a key driver for messaging campaigns intended to drive prosocial behavior such as publicly promoting vaccination and that these campaigns do not necessarily come with adverse experiences for adopters, even for a polarizing issue such as vaccines.

Suggested Citation

  • Nadav Rakocz & Sindhu Ernala & Israel Nir & Udi Weinsberg & Amit Bahl, 2023. "The heterogeneous effects of social support on the adoption of Facebook’s vaccine profile frames feature," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    • Handle: RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-01692-0
    DOI: 10.1057/s41599-023-01692-0
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    1. Tianshu Sun & Sean J. Taylor, 2020. "Displaying things in common to encourage friendship formation: A large randomized field experiment," Quantitative Marketing and Economics (QME), Springer, vol. 18(3), pages 237-271, September.
    2. Sahil Loomba & Alexandre Figueiredo & Simon J. Piatek & Kristen Graaf & Heidi J. Larson, 2021. "Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA," Nature Human Behaviour, Nature, vol. 5(3), pages 337-348, March.
    3. Sinan Aral & Dylan Walker, 2014. "Tie Strength, Embeddedness, and Social Influence: A Large-Scale Networked Experiment," Management Science, INFORMS, vol. 60(6), pages 1352-1370, June.
    4. Agranov, Marina & Elliott, Matt & Ortoleva, Pietro, 2021. "The importance of Social Norms against Strategic Effects: The case of Covid-19 vaccine uptake," Economics Letters, Elsevier, vol. 206(C).
    5. Robert M. Bond & Christopher J. Fariss & Jason J. Jones & Adam D. I. Kramer & Cameron Marlow & Jaime E. Settle & James H. Fowler, 2012. "A 61-million-person experiment in social influence and political mobilization," Nature, Nature, vol. 489(7415), pages 295-298, September.
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