The role of emotion in acquisition of verb meaning

Figures & data

Figure 1. Lexical Semantic Variable Medians, Distributions, and Relationships (n = 2,159).

Note. A. Density plot and boxplot of semantic variables. B. Nonregularized partial-correlation network. Lexical variables are presented in red and semantic variables are presented in blue. Solid purple edges represent positive partial-correlations and dashed orange edges represent negative partial-correlations. The width of the edge line represents the strength of the partial correlation.

Figure 2. Interactions Between Concreteness and Valence and, Separately, Embodiment and Valence, to Predict AoA.

Note. Relationships between valence and age of acquisition for low, mid, and high values of concreteness and, separately, embodiment (Low, mid, and high correspond to the 10th, 50th, and 90th percentile respectively). Blue and red regions represent the 95% confidence band.

Table 1. Regression Models Predicting AoA (n = 2,159).

	Concreteness Model			Embodiment Model
Predictors	Estimates	CI	p	Estimates	CI	p
(Intercept)	9.16	9.08, 9.24	<.001	9.16	9.07, 9.24	<.001
Length	0.36	0.28, 0.45	<.001	0.43	0.34, 0.52	<.001
LgSUBTLWF	−1.23	−1.32, – 1.15	<.001	−1.22	−1.31, – 1.13	<.001
Concreteness	−0.97	−1.05, – 0.88	<.001
Valence (linear)	−4.97	−8.78, – 1.16	.011	−2.89	−7.03, 1.24	.170
Valence (quadratic)	−1.29	−5.08, 2.50	.505	4.02	−0.20, 8.25	.062
Concreteness × Valence (linear)	−4.85	−8.55, – 1.16	.010
Concreteness × Valence (quadratic)	6.92	3.29, 10.55	<.001
Embodiment				−0.70	−0.79, – 0.61	<.001
Embodiment × Valence (linear)				−4.52	−8.54, – 0.51	.027
Embodiment × Valence (quadratic)				1.63	−2.34, 5.59	.421
Observations	2,159			2,159
R^2 / R^2 adjusted	0.478/0.476			0.410/0.408

Note. AoA = Age of acquisition; LgSUBTLWF = log subtitle word frequency.