Effects of semantic neighborhood density in abstract and concrete words

Abstract

Concrete and abstract words are thought to differ along several psycholinguistic variables, such as frequency and emotional content. Here, we consider another variable, semantic neighborhood density, which has received much less attention, likely because semantic neighborhoods of abstract words are difficult to measure. Using a corpus-based method that creates representations of words that emphasize featural information, the current investigation explores the relationship between neighborhood density and concreteness in a large set of English nouns. Two important observations emerge. First, semantic neighborhood density is higher for concrete than for abstract words, even when other variables are accounted for, especially for smaller neighborhood sizes. Second, the effects of semantic neighborhood density on behavior are different for concrete and abstract words. Lexical decision reaction times are fastest for words with sparse neighborhoods; however, this effect is stronger for concrete words than for abstract words. These results suggest that semantic neighborhood density plays a role in the cognitive and psycholinguistic differences between concrete and abstract words, and should be taken into account in studies involving lexical semantics. Furthermore, the pattern of results with the current feature-based neighborhood measure is very different from that with associatively defined neighborhoods, suggesting that these two methods should be treated as separate measures rather than two interchangeable measures of semantic neighborhoods.

The multifaceted abstract brain

“…Emotional arousal and valence are often cited as playing a critical role in the difference between abstract semantics and concrete semantics [7,81,82]. Abstract words, in general, tend to be more emotionally valenced than concrete words [83] and, within the domain of abstract words, highly arousing words elicit different behaviours from emotionally neutral words; the distribution of lexical decision reaction times is narrower and earlier for emotional words [84].…”

“…Semantic richness may be largely a matter of the methods used to measure it, which may be more or less suitable for certain types of concepts. The apparent semantic poverty of abstract concepts may be an artefact of methods suited to evaluating concrete concepts [6,7].…”

“…The particular brain regions involved and the reasons for these differences remain controversial, but the existence of differences is consistent. Neuropsychological double dissociations have pointed to reliance of concrete concepts on featural or taxonomic, and that of abstract concepts on associative or thematic information [7,[9][10][11][12][13] (see [8] for a discussion). With regard to neuroanatomy, a meta-analysis of 19 studies [14] found that two regions were consistently activated for abstract over concrete words or sentences: the left anterior temporal lobe (ATL) and the inferior frontal gyrus (IFG).…”

Word meaning in word identification during reading: Co-occurrence-based semantic neighborhood density effects

“…For example, Danguecan and Buchanan (2016) found that the SND effect (operationalized using WINDSOR; Macdonald, 2013) were consistent for abstract words in comparison to inconsistent SND effect for concrete words across different processing tasks (lexical decision, sentence relatedness, and progressive demasking). As such, the findings of Mirman and Magnuson are only limited to concrete words that have been shown to have inconsistent (or lack of) SND effect compared to abstract words (see Reilly & Desai, 2017).…”

Abstracts 20th International Science of Aphasia Conference, Rome, September 2019

“…Word selection and production can be influenced by several psycholinguistics factors such as word frequency or age of acquisition (e.g. Alario et al, 2004;Newman & German, 2005;Barry et al, 2006;Perret & Bonin, 2018;Rabovsky et al, 2016), or by factors related to the semantic network (Meyer & Schvaneveldt 1971;Ferrand & New, 2003;McRae et al, 2012;Reilly & Desai, 2017;Tree & Hirsh, 2003;Gordon & Cheimariou, 2013). Word production also undergoes changes during lifespan and therefore varies according to the age of the speaker (Kavé et al, 2010;Laganaro et al, 2015).…”