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Social influence aligns peoples' opinions, but social identities and related in-group biases interfere with this alignment. For instance, the recent rise of young climate activists (e.g. `Fridays for Future' or `Last Generation') has highlighted the importance of generational identities in the climate change debate. It is unclear how social identities affect the emergence of opinion patterns, such as consensus or disagreement, in a society. Here, we present an agent-based model to explore this question. Agents communicate in a network and form opinions through social influence. The agents have fixed social identities which involve homophily in their interaction preferences and in-group bias in their perception of others. We find that the in-group bias has opposing effects depending on the network topology. The bias impedes consensus in highly random networks by promoting the formation of echo chambers within social identity groups. In contrast, the bias facilitates consensus in highly clustered networks by aligning dispersed in-group agents across the network and, thereby, preventing the formation of isolated echo chambers. Our model uncovers the mechanisms underpinning these opposing effects of the in-group bias and highlights the importance of the communication network topology for shaping opinion dynamics.

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.

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