Quantifying Conceptual Flexibility in a Compositional Network Model

AbstractA single concept can manifest in many varied forms, depending on the context in which it is activated. That is, concepts appear to be flexible rather than static. Here we implement a compositional model of conceptual knowledge in which basic-level concepts are represented as graph theoretical networks, with the specific goal of quantifying conceptual flexibility. We collect within-concept statistics using online participants, construct network models, and validate these models in a classification analysis. We then extract network measures and find that network diversity and core-periphery structure correspond to conceptual flexibility and stability, respectively. These results suggest that a compositional network model can be used to extract formal measures that are interpretable and useful in the study of conceptual knowledge.

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