A framework to study individual differences in meaning representations

In experimental semantics, researchers are interested in the cognitive processes involved in language processing. The theory in this research area is highly formalized and rich, and usually embedded in formal logic. For instance, looking at the representation of quantifiers, formal logic predicts that the meaning of the quantifiers "more than half" and "most" are identical (i.e., more than 50% for two objects), that the meaning of these quantifiers is unambiguous, and consequently that all individuals will perceive these quantifiers in the same way. While formal logic leads to precise theoretical predictions, a drawback is that it often fails to explain the richness of the observed data. Previous literature has found, for instance, that the quantifier "most" is associated with higher percentages than the quantifier "more than half," that the meaning of "most" is less precisely defined than "more than half," and that individuals vary considerably in their response pattern. In this talk, we present a novel statistical model that captures individual differences in the representation of quantifiers. In addition, the model explains these differences by introducing cognitive processes to the theory such as thresholds, vagueness, and response error. We will illustrate our approach by applying our model to longitudinal data.