<p>Semantic ratings studies have resulted in significant methodological advances towards understanding the importance of experiential information to lexical-semantic processing. Yet, the existing norms are biased towards nouns, with fewer ratings available for verbs. In the present study, we collected new semantic rating norms for 3,512 verbs on the dimensions of concreteness, embodiment, imageability, valence, and arousal. The resulting ratings provide the largest database of verb-specific rating norms across multiple semantic dimensions. They show good reliability and validity on four of five dimensions, with some evident challenges in rating arousal for the verb stimuli. We demonstrate that the norms account for variance in response latencies and accuracy in a lexical decision task, word recognition task, and recognition memory, above and beyond dimensions such as length, frequency, orthographic Levenshtein distance, and age of acquisition, and thus that semantic richness effects are observed in verb processing. The norms described here should be a useful resource for researchers interested in verb lexical-semantic processing.</p>

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English verbs semantic norms database: Concreteness, embodiment, imageability, valence and arousal ratings for 3,500 verbs

  • Emiko J. Muraki,
  • Penny M. Pexman

摘要

Semantic ratings studies have resulted in significant methodological advances towards understanding the importance of experiential information to lexical-semantic processing. Yet, the existing norms are biased towards nouns, with fewer ratings available for verbs. In the present study, we collected new semantic rating norms for 3,512 verbs on the dimensions of concreteness, embodiment, imageability, valence, and arousal. The resulting ratings provide the largest database of verb-specific rating norms across multiple semantic dimensions. They show good reliability and validity on four of five dimensions, with some evident challenges in rating arousal for the verb stimuli. We demonstrate that the norms account for variance in response latencies and accuracy in a lexical decision task, word recognition task, and recognition memory, above and beyond dimensions such as length, frequency, orthographic Levenshtein distance, and age of acquisition, and thus that semantic richness effects are observed in verb processing. The norms described here should be a useful resource for researchers interested in verb lexical-semantic processing.