Abstract
Echo chambers (ECs) are enclosed epistemic circles where like-minded people communicate and reinforce pre-existing beliefs. It remains unclear if cognitive errors are necessarily required for ECs to emerge, and then how ECs are able to persist in networks with available contrary information. We show that ECs can theoretically emerge amongst error-free Bayesian agents, and that larger networks encourage rather than ameliorate EC growth. This suggests that the network structure itself contributes to echo chamber formation. While cognitive and social biases might exacerbate EC emergence, they are not necessary conditions. In line with this, we test stylized interventions to reduce EC formation, finding that system-wide truthful ‘educational’ broadcasts ameliorate the effect, but do not remove it entirely. Such interventions are shown to be more effective on agents newer to the network. Critically, this work serves as a formal argument for the responsibility of system architects in mitigating EC formation and retention.
Highlights
Echo chambers (ECs) are enclosed epistemic circles where like-minded people communicate and reinforce pre-existing beliefs
Simulations were conducted using a broad range of parameter values, and we show results for a representative sample: three search parameter values: α = 0.05, 0.1, 1, and five pruning parameter values: fixed values β = 0.1, 0.5, 1, 2 for ‘confirmatory agents’, and values randomly assigned each time increment, β is ignored by ‘stochastic’ agents
Two social network structures
Summary
Echo chambers (ECs) are enclosed epistemic circles where like-minded people communicate and reinforce pre-existing beliefs. It remains unclear if cognitive errors are necessarily required for ECs to emerge, and how ECs are able to persist in networks with available contrary information. Echo chambers (ECs) can be defined as enclosed epistemic circles where people engage with like-minded others and reinforce their shared pre-existing beliefs. They typically engender high confidence regardless of the veracity of beliefs (conspiratorial thinking (CT) is a good example of this). We test if many rational Bayesian agents, under reasonable constraints of sampling, can grow, maintain, and strengthen ECs in the context of a large social network
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