ArticlePloS one2015
Bayesian decision making in human collectives with binary choices.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Disentangling interaction and bias effects in opinion dynamics of large language models.Nature communications · 2026Article
- Indirect reciprocity with Bayesian reasoning and biases.PLoS computational biology · 2024Article
- Casting votes of antecedents play a key role in successful sequential decision-making.PloS one · 2023Article
- Follow the straggler: zebrafish use a simple heuristic for collective decision-making.Proceedings. Biological sciences · 2020Article
- Inverse Bayesian inference in swarming behaviour of soldier crabs.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2018Article
- Collective Intelligence: Aggregation of Information from Neighbors in a Guessing Game.PloS one · 2016Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Here we focus on the description of the mechanisms behind the process of information aggregation and decision making, a basic step to understand emergent phenomena in society, such as trends, information spreading or the wisdom of crowds. In many situations, agents choose between discrete options. We analyze experimental data on binary opinion choices in humans. The data consists of two separate experiments in which humans answer questions with a binary response, where one is correct and the other is incorrect. The questions are answered without and with information on the answers of some previous participants. We find that a Bayesian approach captures the probability of choosing one of the answers. The influence of peers is uncorrelated with the difficulty of the question. The data is inconsistent with Weber's law, which states that the probability of choosing an option depends on the proportion of previous answers choosing that option and not on the total number of those answers. Last, the present Bayesian model fits reasonably well to the data as compared to some other previously proposed functions although the latter sometime perform slightly better than the Bayesian model. The asset of the present model is the simplicity and mechanistic explanation of the behavior.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.