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ABSTRACT Emotional content of verbal material affects the speed of visual word recognition in various cognitive tasks, independently of lexicosemantic variables. However, little is known about how the dimensions of emotional arousal and valence interact with the lexicosemantic properties of words such as age of acquisition, familiarity, and imageability, that determine word recognition performance. This study aimed to examine these relationships using English ratings for affective and lexicosemantic features. Eighty-two native English speakers rated 300 words for emotional valence, arousal, familiarity, age of acquisition, and imageability. Although both dimensions of emotion were correlated with lexicosemantic variables, a unique emotion cluster produced the strongest quadratic relationship. This finding suggests that emotion should be included in models of word recognition as it is likely to make an independent contribution.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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