Emotion and language: valence and arousal affect word recognition.
Emotion and language: valence and arousal affect word recognition.
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DOI：
10.1037/a0035669
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发表时间：
2014-06
期刊：
影响因子：
--
通讯作者：
Warriner AB
中科院分区：
文献类型：
--
作者：
Kuperman V;Estes Z;Brysbaert M;Warriner AB
情绪影响认知和行为的大多数方面，但情绪因素在当前的单词识别模型中明显缺失。情绪对词汇识别的影响主要是在先前关于对负面刺激的自动警惕的研究中报道的，但这种关系的确切性质尚不清楚。各种自动警觉模型都声称效价对反应时间的影响是分类的，倒U型的，或者与唤醒相互作用的。本研究使用了12，658个单词的样本，包括许多词汇和语义控制因素，以确定唤醒和效价对单词识别的影响的确切性质。从词汇决策和命名的词级和试验级数据中观察到的收敛经验模式表明，效价和唤醒产生独立的单调效应：消极的词比积极的词识别得更慢，唤醒的词比平静的词识别得更慢。效价解释了单词识别延迟的2%的方差，而唤醒的影响较小。效价和唤醒不相互作用，但都与词频相互作用，这样的效价和唤醒发挥更大的影响，在低频词比高频词。这些结果需要一个新的模型的情感文字处理，即程度的消极单调和独立预测的反应速度。这项研究还表明，纳入情感因素，特别是效价，提高了单词识别模型的性能。
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. The present study 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.
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