Discrete emotion norms for 1,122 English words: A database of categorical ratings by Chinese-English bilinguals

Abstract

Although the discrete emotion perspective has gained increasing attention in affective and psycholinguistic research, large-scale normative datasets in a second language (L2) remain limited. To address this gap, the present study introduces a comprehensive database of discrete emotion norms for L2 English. The dataset comprises 1,122 words evaluated by 525 Chinese-English bilinguals across five discrete emotion categories: happiness, anger, fear, disgust and sadness. Participants rated subsets of these words using a 5-point Likert scale. The results demonstrate high inter-rater reliability and reveal systematic relationships between discrete emotion ratings and affective dimensions. Furthermore, these categorical ratings correlate with emotion prototypicality and key psycholinguistic variables, including age of acquisition, word frequency, concreteness and semantic diversity. Distributional analyses highlight a pronounced asymmetry: happiness dominates the semantic space. This database provides detailed discrete emotion ratings for each word and offers a fine-grained tool for selecting controlled stimuli for research on L2 emotion.