The Glasgow Norms: Ratings of 5,500 words on nine scales

Abstract

The Glasgow Norms are a set of normative ratings for 5,553 English words on nine psycholinguistic dimensions: arousal, valence, dominance, concreteness, imageability, familiarity, age of acquisition, semantic size, and gender association. The Glasgow Norms are unique in several respects. First, the corpus itself is relatively large, while simultaneously providing norms across a substantial number of lexical dimensions. Second, for any given subset of words, the same participants provided ratings across all nine dimensions (33 participants/word, on average). Third, two novel dimensions-semantic size and gender association-are included. Finally, the corpus contains a set of 379 ambiguous words that are presented either alone (e.g., toast) or with information that selects an alternative sense (e.g., toast (bread), toast (speech)). The relationships between the dimensions of the Glasgow Norms were initially investigated by assessing their correlations. In addition, a principal component analysis revealed four main factors, accounting for 82% of the variance (Visualization, Emotion, Salience, and Exposure). The validity of the Glasgow Norms was established via comparisons of our ratings to 18 different sets of current psycholinguistic norms. The dimension of size was tested with megastudy data, confirming findings from past studies that have explicitly examined this variable. Alternative senses of ambiguous words (i.e., disambiguated forms), when discordant on a given dimension, seemingly led to appropriately distinct ratings. Informal comparisons between the ratings of ambiguous words and of their alternative senses showed different patterns that likely depended on several factors (the number of senses, their relative strengths, and the rating scales themselves). Overall, the Glasgow Norms provide a valuable resource-in particular, for researchers investigating the role of word recognition in language comprehension.

LexOPS: An R Package and User Interface for the Controlled Generation of Word Stimuli

“…This means that if variables from small corpora, or from multiple corpora with little overlap, are used as independent or control variables, the pool of possible stimuli will be greatly reduced. Similarly, variables are often highly correlated, for instance, as imageability and concreteness are (Scott et al, 2019). It would be Please Note: The final version of this manuscript has now been published with open access in peerreviewed journal, Behavior Research Methods.…”

“…An example box for specifying the levels of an independent variable in the Shiny app. Here, two levels (A1, A2) are being specified for the variable of Familiarity from the Glasgow Norms (Scott et al, 2019). In this case, the density plot shows that the distribution is skewed towards words rated as more familiar, with far fewer words rated as less familiar.…”

Functional specialization of the medial temporal lobes in human recognition memory: dissociating effects of hippocampal vs parahippocampal damage

“…We also included 160 pictures of natural landscapes (targets: n = 80; foils: n = 80), presented in the centre of the display (17 cm wide, 11 cm tall) that were i) not identifiable / known; ii) with no sign of manmade features (buildings, objects), or of people or animals. These images were taken from the royalty-free platform Shutterstock foils: U = 1653.50, p = 0.521) [see 49 for details on ratings of concreteness, imageability, familiarity, age of acquisition, arousal, and valence].…”

“…We used a total of 120 faces (Short Deadline Session: targets: n=30;foils:n=30; Long targets vs. foils: U = 220.5, p = 0.468) ; ix) mean ratings of arousal levels (targets: mean = 4.54, SD =1.05; foils: mean = 4.31; SD = 0.94; targets vs. foils: t = 0.77, p = 0.443); x) mean valence ratings (targets: M = 5.47, IQR = 1.04; foils: M = 5.49; IQR = 0.81; targets vs. foils: U = 242.0, p = 0.809) [see 49 for details on ratings of concreteness, imageability, familiarity, age of acquisition, arousal, and valence]. The same words were presented in the two sessions.…”

How Polysemy Affects Concreteness Ratings: The Case of Metaphor

“…The issue of multiple meanings and concreteness ratings was raised in the early 1980s (e.g., Gilhooly & Logie, 1980a;Toglia & Battig, 1978; see also Theijssen, van Halteren, Boves, & Oostijk, 2011), when research showed that at least 30% of words in English texts have multiple meanings (e.g., Britton, 1978). However, this idea never gained ground in concreteness-ratings studies (exceptions are Gilhooly & Logie, 1980b;Scott, Keitel, Becirspahic, Yao, & Serono, 2019;Wollen, Cox, Coahran, Shea, & Kirby, 1980). When different meanings of the same word refer to equally concrete (or abstract) entities, this may not affect the word's concreteness rating (Theijssen et al, 2011).…”