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Validating Bayesian truth serum in large-scale online human experiments

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  • Morgan R Frank
  • Manuel Cebrian
  • Galen Pickard
  • Iyad Rahwan

Abstract

Bayesian truth serum (BTS) is an exciting new method for improving honesty and information quality in multiple-choice survey, but, despite the method’s mathematical reliance on large sample sizes, existing literature about BTS only focuses on small experiments. Combined with the prevalence of online survey platforms, such as Amazon’s Mechanical Turk, which facilitate surveys with hundreds or thousands of participants, BTS must be effective in large-scale experiments for BTS to become a readily accepted tool in real-world applications. We demonstrate that BTS quantifiably improves honesty in large-scale online surveys where the “honest” distribution of answers is known in expectation on aggregate. Furthermore, we explore a marketing application where “honest” answers cannot be known, but find that BTS treatment impacts the resulting distributions of answers.

Suggested Citation

  • Morgan R Frank & Manuel Cebrian & Galen Pickard & Iyad Rahwan, 2017. "Validating Bayesian truth serum in large-scale online human experiments," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-13, May.
    • Handle: RePEc:plo:pone00:0177385
    DOI: 10.1371/journal.pone.0177385
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    References listed on IDEAS

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    Cited by:

    1. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part I. Integrative synthesis of empirical evidence and conceptualisation of external validity," Papers 2102.02940, arXiv.org.
    2. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    3. Schönegger, Philipp & Verheyen, Steven, 2022. "Taking A Closer Look At The Bayesian Truth Serum: A Registered Report (Stage 2 Registered Report)," OSF Preprints 9zvqj, Center for Open Science.
    4. Charness, Gary & Gneezy, Uri & Rasocha, Vlastimil, 2021. "Experimental methods: Eliciting beliefs," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 234-256.
    5. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part II. Macro-scale analysis of literature and effectiveness of bias mitigation methods," Papers 2102.02945, arXiv.org.
    6. Diarmaid Ó Ceallaigh & Kirsten I.M. Rohde & Hans van Kippersluis, 2024. "Skipping your workout, again? Measuring and understanding time inconsistency in physical activity," Tinbergen Institute Discussion Papers 24-028/V, Tinbergen Institute.

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