Noise and opinion dynamics: How ambiguity promotes pro-majority consensus in the presence of confirmation bias

Peter Steiglechner, Marijn Keijzer, Paul E. Smaldino, Deyshawn Moser et Agostino Merico


Opinion patterns are affected by cognitive biases and noise. While mathematical models have focused extensively on biases, we still know surprisingly little about how different types of noise shape opinion patterns. Here, we use an agent-based opinion dynamics model to investigate the interplay between confirmation bias—represented as bounded confidence—and different types of noise, including a new type: ambiguity noise. While the types of noise considered in the past acted on the agents either before, after, or independent of social interaction, ambiguity noise acts on communicated messages, assuming that the expression of opinions is inherently noisy. We find that noise can induce agreement when the confirmation bias is moderate, but different types of noise lead to quite different conditions for this effect to occur. An application of our model to the climate change debate shows that at just the right mix of confirmation bias and ambiguity noise, opinions tend to converge to a high level of climate change concern. This result is not observed in the absence of noise or with the other types of noise. Our findings highlight the importance of considering and distinguishing between the various types of noise affecting opinion formation and the special role played by ambiguity.


Agent-Based Model; Opinion Formation; Noise; Bounded Confidence; Climate Change; Computational Social Science;

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Royal Society Open Science, 2024, à paraître