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Age-Related Differences in Affective Norms for Chinese Words (AANC).

ABSTRACT: Information on age-related differences in affective meanings of words is widely used by researchers to study emotions, word recognition, attention, memory, and text-based sentiment analysis. To date, no Chinese affective norms for older adults are available although Chinese as a spoken language has the largest population in the world. This article presents the first large-scale age-related affective norms for 2,061 four-character Chinese words (AANC). Each word in this database has rating values in the four dimensions, namely, valence, arousal, dominance, and familiarity. We found that older adults tended to perceive positive words as more arousing and less controllable and evaluate negative words as less arousing and more controllable than younger adults did. This indicates that the positivity effect is reliable for older adults who show a processing bias toward positive vs. negative words. Our AANC database supplies valuable information for researchers to study how emotional characteristics of words influence the cognitive processes and how this influence evolves with age. This age-related difference study on affective norms not only provides a tool for cognitive science, gerontology, and psychology in experimental studies but also serves as a valuable resource for affective analysis in various natural language processing applications.

SUBMITTER: Liu P

PROVIDER: S-EPMC8082186 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Emotion concepts are built through situated experience. Abstract word meaning is grounded in this affective knowledge, giving words the potential to evoke emotional feelings and reactions (e.g., Vigliocco et al., 2009). In the present work we explore whether words differ in the extent to which they evoke 'specific' emotional knowledge. Using a categorical approach, in which an affective 'context' is created, it is possible to assess whether words proportionally activate knowledge relevant to different emotional states (e.g., 'sadness', 'anger', Stevenson, Mikels & James, 2007a). We argue that this method may be particularly effective when assessing the emotional meaning of action words (e.g., Schacht & Sommer, 2009). In study 1 we use a constrained feature generation task to derive a set of action words that participants associated with six, basic emotional states (see full list in Appendix S1). Generation frequencies were taken to indicate the likelihood that the word would evoke emotional knowledge relevant to the state to which it had been paired. In study 2 a rating task was used to assess the strength of association between the six most frequently generated, or 'typical', action words and corresponding emotion labels. Participants were presented with a series of sentences, in which action words (typical and atypical) and labels were paired e.g., "If you are feeling 'sad' how likely would you be to act in the following way?" … 'cry.' Findings suggest that typical associations were robust. Participants always gave higher ratings to typical vs. atypical action word and label pairings, even when (a) rating direction was manipulated (the label or verb appeared first in the sentence), and (b) the typical behaviours were to be performed by the rater themselves, or others. Our findings suggest that emotion-related action words vary in the extent to which they evoke knowledge relevant for different emotional states. When measuring affective grounding, it may then be appropriate to use categorical ratings in conjunction with unimodal measures, which assess the 'magnitude' to which words evoke feelings (e.g., Newcombe et al., 2012). Towards this aim we provide a set of emotion-related action words, accompanied by generation frequency and rating data, which show how strongly each word evokes knowledge relevant to basic emotional states.

Dataset Information

Age-Related Differences in Affective Norms for Chinese Words (AANC).

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