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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/21816
Title: Emotion and Language: Valence and Arousal Affect Word Recognition
Authors: Kuperman, Victor
Estes, Zachary
Brysbaert, Marc
Warriner, Amy Beth
Department: None
Keywords: Arousal and valence;Automatic vigilance;Emotion;Lexical decision and naming;Word recognition
Publication Date: Jun-2014
Publisher: American Psychological Association
Citation: Kuperman, V., Estes, Z., Brysbaert, M., & Warriner, A. (2014). Emotion and language: Valence and arousal affect word recognition. Journal of Experimental Psychology: General, 143(3), 1065–1081. https://doi.org/10.1037/a0035669
Abstract: Emotion influences most aspects of cognition and behavior, but emotional factors are conspicuously absent from current models of word recognition. The influence of emotion on word recognition has mostly been reported in prior studies on the automatic vigilance for negative stimuli, but the precise nature of this relationship is unclear. Various models of automatic vigilance have claimed that the effect of valence on response times is categorical, an inverted U, or interactive with arousal. In the present study, we used a sample of 12,658 words and included many lexical and semantic control factors to determine the precise nature of the effects of arousal and valence on word recognition. Converging empirical patterns observed in word-level and trial-level data from lexical decision and naming indicate that valence and arousal exert independent monotonic effects: Negative words are recognized more slowly than positive words, and arousing words are recognized more slowly than calming words. Valence explained about 2% of the variance in word recognition latencies, whereas the effect of arousal was smaller. Valence and arousal do not interact, but both interact with word frequency, such that valence and arousal exert larger effects among low-frequency words than among high-frequency words. These results necessitate a new model of affective word processing whereby the degree of negativity monotonically and independently predicts the speed of responding. This research also demonstrates that incorporating emotional factors, especially valence, improves the performance of models of word recognition.
URI: http://hdl.handle.net/11375/21816
Identifier: https://doi.org/10.1037/a0035669
Appears in Collections:Representative Publications from ARiEAL

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