<p>Ratings for the following factors were based on separate 100-point scales (low to high): Concreteness (abstract to concrete), Semantic Size (small to large), Arousal (unarousing to arousing), Raw Valence (negative to positive), and Age of Acquisition (early to late). Absolute Valence was calculated via the following transformations: (a) shifting the 0 to 100 scale to a −50 to +50 scale (to more appropriately represent valence); (b) taking the absolute value of each rating (resulting in a 50-point scale); and (c) doubling each value to obtain a 100-point scale (from low to high unsigned valence). Word Frequency is expressed in occurrences per million and Word Length in number of letters.</p
We compared the quality of prediction of word variables based on a Dutch word association and text c...
<p>Note: WS refers to word structure judgment task and WT refers to word tone judgment task.</p
Mean accuracy rates and standard deviations (by speaker) for different word types across different r...
Abstract: Subjective ratings of dimensions of lexical meaning have long been used in experimental ps...
<p>Target word norms [mean and standard deviation (SD)] according to the 2×2 experimental manipulati...
Supplementary Materials: Excel sheet showing focal vocabulary items and data These materials consist...
A sample of 50 words taken from an American frequency count was used in obtaining subjective estimat...
<p><i>Note.</i> The valence and arousal groups were created as follows: low/negative score range 1–3...
Human ratings of valence, arousal, and dominance are frequently used to study the cognitive mechanis...
1<p>Min and max ratings are indicated in parenthesis. Standard Deviation is indicated in italics bel...
Mean accuracy rates and standard deviations (by speaker) for different word types across different r...
Mean strength ratings (0–5) for the monosyllabic words, 95% confidence intervals, and standard devia...
Reliability of valence, arousal, and comprehensibility ratings for English texts and the texts in th...
Mean accuracy rates and standard deviations (by speaker) for different word types across different r...
<p><i>Note</i>. Word Frequency is the log-transformed number of contexts in which a certain word occ...
We compared the quality of prediction of word variables based on a Dutch word association and text c...
<p>Note: WS refers to word structure judgment task and WT refers to word tone judgment task.</p
Mean accuracy rates and standard deviations (by speaker) for different word types across different r...
Abstract: Subjective ratings of dimensions of lexical meaning have long been used in experimental ps...
<p>Target word norms [mean and standard deviation (SD)] according to the 2×2 experimental manipulati...
Supplementary Materials: Excel sheet showing focal vocabulary items and data These materials consist...
A sample of 50 words taken from an American frequency count was used in obtaining subjective estimat...
<p><i>Note.</i> The valence and arousal groups were created as follows: low/negative score range 1–3...
Human ratings of valence, arousal, and dominance are frequently used to study the cognitive mechanis...
1<p>Min and max ratings are indicated in parenthesis. Standard Deviation is indicated in italics bel...
Mean accuracy rates and standard deviations (by speaker) for different word types across different r...
Mean strength ratings (0–5) for the monosyllabic words, 95% confidence intervals, and standard devia...
Reliability of valence, arousal, and comprehensibility ratings for English texts and the texts in th...
Mean accuracy rates and standard deviations (by speaker) for different word types across different r...
<p><i>Note</i>. Word Frequency is the log-transformed number of contexts in which a certain word occ...
We compared the quality of prediction of word variables based on a Dutch word association and text c...
<p>Note: WS refers to word structure judgment task and WT refers to word tone judgment task.</p
Mean accuracy rates and standard deviations (by speaker) for different word types across different r...