ArticleBehavior research methods2026
Affective norms for Chinese words in ten discrete emotion categories.
Article in Behavior research methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Emotion in English as a foreign language: Affective ratings for over 2,000 words by college learners.Behavior research methods · 2026Article
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Abstract
The present study provides the first affective norm for 3,783 Chinese words for ten discrete emotions: happiness, anger, sadness, fear, disgust, anxiety, surprise, contentment, amusement, and serenity. Ratings of words were collected from a total of 797 native speakers of Chinese using five-point Likert scales. A total of 895,858 valid ratings were collected. Results showed high inter-rater reliability and sufficient validity. This database shows an unequal distribution across the ten discrete emotions, with a total of 361 (9.54%) "neutral" words (words with an average rating of less than 3 in the ten discrete emotions), 2,482 (65.61%) "pure" words (words with an average rating of 3 or higher in only one discrete emotion), and 940 (24.85%) "mixed" words (words with an average rating of 3 or higher in more than one discrete emotion). The highest percentage of pure words was in the discrete emotion of serenity; a mixed word can be related to at most six different discrete emotions. Analyses revealed significant relationships between discrete emotions, affective dimensions (valence and arousal), and psycholinguistic variables (e.g., objective frequency, subjective frequency, familiarity, age of acquisition, concreteness, imageability, sensory experience rating, and emotional prototypicality). Small but significant individual differences in gender and personality were also revealed. To date, this new database is the largest set of ratings of ten discrete emotion categories in any language, and can serve as a valuable resource in studies of language, emotion, and cognition. The norms are available at https://osf.io/uztvh/?view_only=3d56e6dfcfb043eba2d3fb850ee27f68 .
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