Valence and arousal ratings for 11,310 simplified Chinese words

Xu, Xu; Li, Jiayin; Chen, Huilin

doi:10.3758/s13428-021-01607-4

Cited by 36 publications

(28 citation statements)

References 65 publications

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Section: Validity Of the Subjective Rating Datasetmentioning

confidence: 99%

“…For the semantic dimension of emotion (valence), the ratings were validated based on Xu et al 55 and Binder et al 1 . The instructions used in the current study and Xu et al 55 are similar, and the correlation between the two studies is 0.935. The emotion ratings of the current study are closely associated with two dimensions of Binder et al 1 , that is Pleasant and Unpleasant.…”

Section: Validity Of the Subjective Rating Datasetmentioning

confidence: 99%

“…The absolute value of valence rating has been used to represent arousal in some previous studies 57 . We correlated the absolute values of our emotion ratings with the arousal ratings provided in Xu et al 55 and Binder et al 1 . The correlations are 0.585 and 0.532, respectively, which is consistent with the findings in the literature.…”

Section: Validity Of the Subjective Rating Datasetmentioning

confidence: 99%

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A large dataset of semantic ratings and its computational extension

et al. 2023

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Evidence from psychology and cognitive neuroscience indicates that the human brain’s semantic system contains several specific subsystems, each representing a particular dimension of semantic information. Word ratings on these different semantic dimensions can help investigate the behavioral and neural impacts of semantic dimensions on language processes and build computational representations of language meaning according to the semantic space of the human cognitive system. Existing semantic rating databases provide ratings for hundreds to thousands of words, which can hardly support a comprehensive semantic analysis of natural texts or speech. This article reports a large database, the Six Semantic Dimension Database (SSDD), which contains subjective ratings for 17,940 commonly used Chinese words on six major semantic dimensions: vision, motor, socialness, emotion, time, and space. Furthermore, using computational models to learn the mapping relations between subjective ratings and word embeddings, we include the estimated semantic ratings for 1,427,992 Chinese and 1,515,633 English words in the SSDD. The SSDD will aid studies on natural language processing, text analysis, and semantic representation in the brain.

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Section: Validity Of the Subjective Rating Datasetmentioning

confidence: 99%

Section: Validity Of the Subjective Rating Datasetmentioning

confidence: 99%

Section: Validity Of the Subjective Rating Datasetmentioning

confidence: 99%

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A large dataset of semantic ratings and its computational extension

et al. 2023

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“…The shape of the relationship between arousal and valence can also be influenced by culture, and it has been shown that the increase in the steepness of the function is determined by the level of extroversion of a given culture and the distinction between eastern and western cultures (Kuppens et al, 2017). In fact, recent studies on Chinese words have shown that differences in the evaluation of valence between Chinese and English words may be determined by cultural and socio-political factors (Xu et al, 2022).…”

Section: Emotions Influencing Cognitive Controlmentioning

confidence: 99%

Role of arousal, subjective significance and valence of affect in task-switching effectiveness

et al. 2023

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Switching between two concurrent tasks is an important ability of the mind. In a series of two experiments, we explored the role of activation (arousal and subjective significance) and emotional valence in shaping the effectiveness of switching between two cognitive tasks: gender-marking and emotional categorisations of verbal stimuli. We expected arousal to disrupt and subjective significance to boost the effectiveness of cognitive switching. We employed a paradigm that allowed us to present emotional words and measure the reaction latencies when a task given to the participants was switched; thus, the response was more costly than when continuing to respond to the same task. The first experiment, conducted with neutral words, showed that high subjective significance reduced reaction latencies in comparison with medium subjective significance. The second experiment showed a similar pattern only for neutral stimuli in the emotional categorisation task, but not for negative and positive stimuli. We did not find a clear effect of arousal or valence. The results of our studies suggest that subjective significance is independent of arousal in enhancing the cognitive control resources.

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“…Valence can be positive or negative and corresponds to the standard dimension of sentiment analysis; Arousal, which can be low or high and express the degree (Vorakitphan et al, 2020). We use the VA score annotated by Xu et al (2021), which contains 11,310 simplified Chinese words. The valence and arousal ratings include scores -3 to +3 for valence rating and scores 0 to 4 for arousal rating.…”

Section: Differences Between Complaints and Sentimentmentioning

confidence: 99%

Analyzing the Intensity of Complaints on Social Media

Fang¹,

Zong²,

Li³

et al. 2022

Preprint

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Complaining is a speech act that expresses a negative inconsistency between reality and human expectations. While prior studies mostly focus on identifying the existence or the type of complaints, in this work, we present the first study in computational linguistics of measuring the intensity of complaints from text. Analyzing complaints from such perspective is particularly useful, as complaints of certain degrees may cause severe consequences for companies or organizations. We create the first Chinese dataset containing 3,103 posts about complaints from Weibo, a popular Chinese social media platform. These posts are then annotated with complaints intensity scores using Best-Worst Scaling (BWS) method. We show that complaints intensity can be accurately estimated by computational models with the best mean square error achieving 0.11. Furthermore, we conduct a comprehensive linguistic analysis around complaints, including the connections between complaints and sentiment, and a cross-lingual comparison for complaints expressions used by Chinese and English speakers. We finally show that our complaints intensity scores can be incorporated for better estimating the popularity of posts on social media. 1

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Valence and arousal ratings for 11,310 simplified Chinese words

Cited by 36 publications

References 65 publications

A large dataset of semantic ratings and its computational extension

A large dataset of semantic ratings and its computational extension

Role of arousal, subjective significance and valence of affect in task-switching effectiveness

Analyzing the Intensity of Complaints on Social Media

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