Evidence map›Paper›PMID 36754941›Full record

ArticleBehavior research methods2024

Sentiment annotations for 3827 simplified Chinese characters.

Cheng Peng, Xu Xu, Zhen Bao

Abstract read
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Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Cheng Peng *Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Xu Xu *Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China. xu2xu3@gmail.com.
Zhen BaoShanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sentiment analysis in Chinese natural language processing has been largely based on words annotated with sentiment categories or scores. Characters, however, are the basic orthographic, phonological, and in most cases, semantic units in the Chinese language. This study collected sentiment annotations for 3827 characters. The ratings demonstrated high levels of reliability, and were validated through a comparison with the ratings of some characters' word equivalents reported in a previous norming study. Relations with other lexico-semantic variables and character processing efficiency were investigated. Furthermore, analyses of the association between constituent character valence and word valence revealed semantic compositionality and sentiment fusion characteristic of larger Chinese linguistic units. These ratings for characters, expanding current Chinese sentiment lexicons, can be utilized for the purposes of more precise stimuli assessment in research on Chinese character processing and more efficient sentiment analysis equipped with annotations of single-character words.

Indexed as

LanguageSemanticsAttitudeHumansLinguisticsReadingReproducibility of ResultsAffect representationChinese charactersSentiment compositionalityValence

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.