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The role of tie strength in assessing credibility of scientific content on facebook

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  • Hershkovitz, Arnon
  • Hayat, Zack

Abstract

Social networking sites have become a major venue for dissemination of- and discussions about science-related topics. On these platforms, message credibility assessment takes into account not only traditional cues (like scientific arguments and information source), but also new types of social cues. Of the latter, we focus on tie strength, a central component of social networking sites, which has an important role in information flow, and the role of which in the process of message credibility assessment has been so far overlooked. We also consider two important and relevant meta-cognitive measures: need for cognition and expertise perception. Applying an experimental design in Facebook (N = 324), our findings suggest that need for cognition weakens the positive associations between tie strength and perceived message credibility. Also, both expertise perception and tie strength have positive effect on perceived message credibility.

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  • Hershkovitz, Arnon & Hayat, Zack, 2020. "The role of tie strength in assessing credibility of scientific content on facebook," Technology in Society, Elsevier, vol. 61(C).
    • Handle: RePEc:eee:teinso:v:61:y:2020:i:c:s0160791x19304099
    DOI: 10.1016/j.techsoc.2020.101261
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    References listed on IDEAS

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    1. Ricard L. Fogués & Jose M. Such & Agustin Espinosa & Ana Garcia-Fornes, 2014. "BFF: A tool for eliciting tie strength and user communities in social networking services," Information Systems Frontiers, Springer, vol. 16(2), pages 225-237, April.
    2. Nicole C. Krämer & Leonie Rösner & Sabrina C. Eimler & Stephan Winter & German Neubaum, 2014. "Let the Weakest Link Go! Empirical Explorations on the Relative Importance of Weak and Strong Ties on Social Networking Sites," Societies, MDPI, vol. 4(4), pages 1-25, December.
    3. Miriam J. Metzger, 2007. "Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(13), pages 2078-2091, November.
    4. Friederike Hendriks & Dorothe Kienhues & Rainer Bromme, 2015. "Measuring Laypeople’s Trust in Experts in a Digital Age: The Muenster Epistemic Trustworthiness Inventory (METI)," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-20, October.
    5. Brown, Genavee & Michinov, Nicolas, 2019. "Measuring latent ties on Facebook: A novel approach to studying their prevalence and relationship with bridging social capital," Technology in Society, Elsevier, vol. 59(C).
    6. Daniel Z. Levin & Rob Cross, 2004. "The Strength of Weak Ties You Can Trust: The Mediating Role of Trust in Effective Knowledge Transfer," Management Science, INFORMS, vol. 50(11), pages 1477-1490, November.
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    Cited by:

    1. Xiao, Lin & Li, Xiaofeng & Zhang, Yucheng, 2023. "Exploring the factors influencing consumer engagement behavior regarding short-form video advertising: A big data perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    2. Moshkovitz, Karin & Hayat, Tsahi, 2021. "The rich get richer: Extroverts' social capital on twitter," Technology in Society, Elsevier, vol. 65(C).

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