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Bayesian Generalization of Emojis
Abstract
We explore how attributes and relations contribute to generalization of a property across stimuli for ecologically validstimuli used often to communicate: emojis. We use the Bayesian Generalization Framework to model generalizationjudgments from given triplets of emojis to new triplets of emojis that share either a common relation, common attribute,both, or neither. Based on the model predictions, we conducted a behavioral experiment investigating the strength ofattributes and relations when generalizing across emojis. The model learned to use attributes or relations appropriately;however when given triplets that share both a common attribute and relation, it gave more weight to the common attributesthan human participants did. This suggests that people are strongly, but not completely, biased towards using relationswhen generalizing a novel property across triplets of emojis.
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