Emotion in language: Emotion word type and valence interactively predicted Chinese emotional word processing in emotion categorization task

Abstract

AbstractThe present study examined the predicted effects of emotion word type and valence on emotional word recognition and explored their influence on emotion effects through an emotion categorization task. The results showed the influence of emotion word type and valence on emotional words recognition. Emotion‐label words exhibited faster response and higher accuracy rates (ACC) than emotion‐laden words, and positive words evoked faster response and lower ACC than negative words. Positive emotion‐label words and negative emotion‐laden words evoked higher ACC than negative emotion‐label words and positive emotion‐laden words. Besides, the findings revealed the modulation of emotion word type and valence on the emotion effects. Emotion‐label words and positive words displayed larger emotion effects than emotion‐laden words and negative words in reaction time, and only emotion‐laden words and positive emotion‐label words showed emotion effects in ACC. These findings endorsed the mediated emotion concept account, density hypothesis, and automatic vigilance hypothesis. Based on the findings, we proposed a valence cognition account to explain the interactive results.