Constraints on observing actions and limited attention in collective decisions spontaneously form echo chambers that lock groups into inaccurate states and make accuracy highly sensitive to social weighting.
MIT press, 2005
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Recurrent networks built from tunable expressive neurons reveal scaling laws with an optimal parameter split that shifts toward higher per-neuron complexity at larger scales.
citing papers explorer
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Messaging strategies and the emergence of echo chambers in collective decision-making
Constraints on observing actions and limited attention in collective decisions spontaneously form echo chambers that lock groups into inaccurate states and make accuracy highly sensitive to social weighting.
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Scaling Laws and Tradeoffs in Recurrent Networks of Expressive Neurons
Recurrent networks built from tunable expressive neurons reveal scaling laws with an optimal parameter split that shifts toward higher per-neuron complexity at larger scales.