Concreteness ratings for 62 thousand English multiword expressions

Abstract

Concreteness describes the degree to which a word’s meaning is understood through perception and action. The Brysbaert et al. (2014) concreteness ratings have provided insight into language processing and text analysis. However, these ratings are limited to English single words and a few two-word expressions. Increasingly, attention is focused on the importance of multiword expressions, given their centrality in everyday language use and language acquisition. We present concreteness ratings for 62,889 multiword expressions and examine their relationship to the existing concreteness ratings for single words and two-word expressions. These new ratings represent the first big dataset of multiword expressions, and will be useful for researchers interested in language acquisition and language processing, as well as natural language processing and textual analysis.

Linguistic concreteness of statements of true and false intentions.

“…It is also possible that automated computer analysis of concreteness is not yet sufficiently developed for this purpose. One way around the limitation of simple word count methods is to use concreteness ratings of multiword expressions, which have recently been developed (Muraki et al, 2022). Another option is to use human coders.…”

Semantic variables and their application in L2 research

“…Despite existing for more than sixty years, researchers continue to publish concreteness ratings and apply them in the study of linguistic processing. Due to the ease of collecting data through crowdsourcing, researchers are now able to obtain massive datasets of ratings, such as Brysbaert's et al's (2014) ratings for 40,000 English words and Muraki et al's (2022) database of rating for 62,000 multiword expressions. Ratings for languages other than English are available, such as Spanish ratings in the EsPal database (Duchon et al, 2013) or Croatian ratings (Ćoso et al, 2019).…”

Investigating the Nature of Disagreements on Mid-Scale Ratings: A Case Study on the Abstractness-Concreteness Continuum

“…For example, the Brysbaert norms rely on isolated target presentation, and part-of-speech information was added post-hoc from the SUBTLEX-US corpus (Brysbaert et al, 2012). Muraki et al (2022) used the same setup as Brysbaert et al (2014) but for multiword expressions, in which case part-ofspeech ambiguity did not arise, but the targets were also presented out of context. Despite these problems, ratings on a scale still remain the major strategy to collect human judgements on degrees of semantic variables, while alternatives such as best-worst scaling are available (Kiritchenko and Mohammad, 2017;Abdalla et al, 2023).…”