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. 2025 Jul 15;57(8):224.
doi: 10.3758/s13428-025-02753-9.

Unveiling the intensity-ambiguity relationships among affective and lexico-semantic variables in Chinese characters and the character-word relationships in Chinese two-character words

Xi Cheng  1 , Chi-Shing Tse  2   3 , Yuen-Lai Chan  4 , Kai Yan Lau  5 , Yen Na Yum  6
Affiliations

Unveiling the intensity-ambiguity relationships among affective and lexico-semantic variables in Chinese characters and the character-word relationships in Chinese two-character words

Xi Cheng et al. Behav Res Methods. .

Erratum in

Abstract

Understanding the lexical characteristics of Chinese characters is crucial given their extensive usage and unique logographic structure. In this study, we normed affective ratings (valence and arousal) for 3971 Chinese characters. We investigated the relationships between intensity (mean rating) and ambiguity (rating variability) of these affective variables, alongside additional lexico-semantic variables from Su et al., Behavior Research Methods, 55(6), 2989-3008, (2022). Drawing on lexical data from 25,281 two-character words available in the Chinese Lexicon Project (Tse et al., Behavior Research Methods, 49(4), 1503-1519, 2017, Behavior Research Methods, 55(8), 4382-4402, 2023; Chan & Tse, Behavior Research Methods, 56(7), 7574-7601, 2024), we further explored cross-level relationships between character-level and word-level variables. Multiple regression analyses controlling for various lexical variables revealed several noteworthy patterns. First, we identified a quadratic valence-arousal relationship, such that characters with extreme valence ratings (either highly positive or highly negative) elicited higher arousal compared to neutral characters. This relationship was moderated by arousal ambiguity, partially consistent with previous findings (Brainerd et al. Journal of Experimental Psychology: General, 150(8), 1476-1499, 2021a), Second, we observed consistent quadratic intensity-ambiguity relationships across all variables, supporting the quadratic law proposed by Brainerd et al. Journal of Memory and Language, 121, 104286, (2021b). Finally, significant positive associations occurred between character-level variables and their corresponding word-level variables for both the first and second characters. The strength of these cross-level relationships varied across affective and lexico-semantic variables and may further be influenced by semantic transparency. Overall, our findings advance the understanding of affective and semantic features of Chinese characters and offer insights into the cross-level integration of characters' and words' lexical characteristics. The data reported in this paper are available at: https://osf.io/kh4yx .

Keywords: Chinese Characters; Megastudy; Norming; Valence.

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Conflict of interest statement

Declarations. Conflicts of interest/Competing interests: On behalf of all authors, the corresponding author states that there is no conflict of interest. Ethics approval: This study was approved by the Survey and Behavioral Research Ethics Committee at the Chinese University of Hong Kong (SBRE-23-0238) and was conducted in accordance with relevant guidelines and in accordance with the Declaration of Helsinki. Consent to participate: Prior to their participation in the study, all participants provided informed consent. Consent for publication: All authors approve for this publication.

Figures

Fig. 1
Fig. 1
Distribution of mean and ambiguities of valence and arousal. Note. Top left: Distributions of valence and arousal ratings. Top right: Distributions of valence and arousal ambiguities. Bottom left: Scatterplots for the variability of valence. Bottom right: Scatterplot for the variability of arousal. Dashed lines indicate medians
Fig. 2
Fig. 2
Relationships between valence and other lexico-semantic variables
Fig. 3
Fig. 3
Relationships between arousal and other lexico-semantic variables
Fig. 4
Fig. 4
Familiarity–concreteness relationship
Fig. 5
Fig. 5
Familiarity–imageability relationship
Fig. 6
Fig. 6
Familiarity–age-of-acquisition relationship
Fig. 7
Fig. 7
Concreteness–imageability relationship
Fig. 8
Fig. 8
Concreteness–age-of-acquisition relationship
Fig. 9
Fig. 9
Imageability–age-of-acquisition relationship
Fig. 10
Fig. 10
Intensity–valence ambiguity relationships
Fig. 11
Fig. 11
Valence–arousal relationship moderated by valence ambiguity
Fig. 12
Fig. 12
Valence–arousal relationship moderated by arousal ambiguity
Fig. 13
Fig. 13
Valence–valence ambiguity
Fig. 14
Fig. 14
Arousal–arousal ambiguity
Fig. 15
Fig. 15
Familiarity–familiarity ambiguity
Fig. 16
Fig. 16
Concreteness–concreteness ambiguity
Fig. 17
Fig. 17
Imageability–imageability ambiguity
Fig. 18
Fig. 18
Age of acquisition–age of acquisition ambiguity
Fig. 19
Fig. 19
Character valence–word valence relationship. Note. The two figures at the bottom present the moderation effect of character semantic transparency in the character valence–word valence relationship
Fig. 20
Fig. 20
Character arousal–word arousal. Note. The two figures at the bottom present the moderation effect of character semantic transparency in the character arousal–word arousal relationship
Fig. 21
Fig. 21
Character familiarity–word familiarity. Note. The two figures at the bottom present the moderation effect of character semantic transparency in the character familiarity–word familiarity relationship
Fig. 22
Fig. 22
Character concreteness–word concreteness. Note. The two figures at the bottom present the moderation effect of character semantic transparency in the character concreteness–word concreteness relationship
Fig. 23
Fig. 23
Character imageability–word imageability. Note. The two figures at the bottom present the moderation effect of character semantic transparency in the character imageability–word imageability relationship
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