Clustering, hierarchical organization, and the topography of abstract and concrete nouns

Abstract

The empirical study of language has historically relied heavily upon concrete word stimuli. By definition, concrete words evoke salient perceptual associations that fit well within feature-based, sensorimotor models of word meaning. In contrast, many theorists argue that abstract words are “disembodied” in that their meaning is mediated through language. We investigated word meaning as distributed in multidimensional space using hierarchical cluster analysis. Participants (N = 365) rated target words (n = 400 English nouns) across 12 cognitive dimensions (e.g., polarity, ease of teaching, emotional valence). Factor reduction revealed three latent factors, corresponding roughly to perceptual salience, affective association, and magnitude. We plotted the original 400 words for the three latent factors. Abstract and concrete words showed overlap in their topography but also differentiated themselves in semantic space. This topographic approach to word meaning offers a unique perspective to word concreteness.

Toward a brain-based componential semantic representation

“…Many abstract concepts refer specifically to cognitive events or states (think, believe, know, doubt, reason) or to products of cognition (concept, theory, idea, whim). Abstract concepts also tend to have stronger affective content than do concrete concepts (Borghi et al, 2011;Kousta et al, 2011;Troche et al, 2014;Vigliocco et al, 2009;Zdrazilova & Pexman, 2013), which may explain the selective engagement of anterior temporal regions by abstract relative to concrete concepts in many neuroimaging studies (see Binder, 2007;Binder et al, 2009, for reviews). Many so-called abstract concepts refer specifically to affective states or qualities (anger, fear, sad, happy, disgust).…”

“…These representations successfully predicted performance by a severely aphasic patient on an abstract noun comprehension task in which semantic similarity between target and foil responses was manipulated, whereas similarity metrics (latent semantic analysis cosine similarity) based on patterns of word usage (Landauer & Dumais, 1997) were not predictive (Crutch, Troche, Reilly, & Ridgway, 2013). Troche et al (Troche, Crutch, & Reilly, 2014) provide further analyses of these representations, identifying three latent factors (labelled perceptual salience, affective association, and magnitude) that accounted for 81% of the variance. Abstract nouns were rated higher than concrete nouns on the dimensions of emotion, polarity, social interaction, morality, and space.…”

Reference, Phases and Individuation: Topics at the Labeling-Interpretive Interface

“…Further to this, empirical, topographic approaches to concept clustering (Troche et al 2014, Pollock 2014) provide reason to believe that the conceptual basis for abstract words like justice and morality extends beyond the lexicon. 7 Gärdenfors and Osvath (2005) have also argued that nonhumans do not actually 'plan' at all (contra Emery & Clayton 2004).…”

Three symbol ungrounding problems: Abstract concepts and the future of embodied cognition

“…One of the important features of the semantic-richness research is that the effects associated with different dimensions are often task-dependent Moffat et al, 2015;Siakaluk, Knol, & Pexman, 2014;Zdrazilova & Pexman, 2013). Troche, Crutch, and Reilly (2014) have offered a different defense of a multidimensional approach to abstract concepts. Rather than rely on an intuitive notion of abstractness, they investigated how the meanings of 400 concrete and abstract English nouns are distributed in a multidimensional space using hierarchical cluster analysis.…”