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English Verb Embodiment Ratings

Source: R/data.R
english_verb_embodiment.Rd

A dataset of embodiment and semantic norms for 2,938 English verbs, including embodiment, concreteness, imageability, valence, and arousal ratings. Each dimension includes mean, standard deviation, and number of raters.

Format

A data frame with 2938 rows and 17 variables.

Source

Muraki, E.J. & Pexman, P.M. (2025). English verb semantic norms database. Behavior Research Methods, 57, 8480–8503. doi:10.3758/s13428-025-02675-6

Details

Embodiment captures the degree to which a word's meaning is grounded in bodily experience. Unlike the Lancaster Sensorimotor Norms (which break perception into separate channels), embodiment provides a single holistic rating of physical-bodily engagement for each verb.

This dictionary complements sensorimotor (which covers 39,707 words across all parts of speech with channel-specific ratings) and concreteness (which covers 39,954 lemmas). The embodiment and verb-specific imageability ratings are novel dimensions not available in any other dictionary in this package. Concreteness, valence, and arousal overlap with existing dictionaries but are included here for completeness and internal consistency within the verb-specific dataset.

Note: 79 verbs have missing embodiment ratings (NA) because too few raters provided numeric responses.

Variables

  • term. the English verb (lowercase)

  • embodiment_mean. mean embodiment rating (1–7 scale; NA for 79 verbs)

  • embodiment_sd. standard deviation of embodiment ratings

  • embodiment_n. number of raters providing numeric embodiment responses

  • concreteness_mean. mean concreteness rating (1–5 scale)

  • concreteness_sd. standard deviation of concreteness ratings

  • concreteness_n. number of raters providing numeric concreteness responses

  • imageability_mean. mean imageability rating (1–7 scale)

  • imageability_sd. standard deviation of imageability ratings

  • imageability_n. number of raters providing numeric imageability responses

  • valence_mean. mean valence rating (1–9 scale)

  • valence_sd. standard deviation of valence ratings

  • valence_n. number of raters providing numeric valence responses

  • arousal_mean. mean arousal rating (1–9 scale)

  • arousal_sd. standard deviation of arousal ratings

  • arousal_n. number of raters providing numeric arousal responses

  • source. data source attribution ("muraki_pexman_2025")