Nearest Neighbor Analysis of Psychological Spaces
نویسندگان
چکیده
Geometric models impose an upper bound on the number of points that can share the same nearest neighbor. A much more restrictive bound is implied by the assumption that the data points represent a sample from some continuous distribution in a multidimensional Euclidean space. The analysis of 100 data sets shows that most perceptual data satisfy the geometric-statistical bound whereas many conceptual data sets exceed it. The most striking discrepancies between the data and their multidimensional representations arise in semantic fields when the stimulus set includes a focal element (e.g., a superordinate category) that is the nearest neighbor of many of its instances. Theoretical and methodological implications of nearest neighbor analysis are discussed.
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