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A Contrastive Study of Semantic Prosody Based on Sentiment Analysis: The Case of Adverbs of Completeness in English and Chinese

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Udgivet i:The Educational Review, USA vol. 9, no. 9 (2025), p. 780-786
Hovedforfatter: Ding, Guoqi
Andre forfattere: Zhu, Yuanxuan
Udgivet:
Hill Publishing Group Inc
Fag:
Dictionaries
English language
Lexicalization
Adverbs
Social networks
Polarity
Syntactic analysis
Semantic analysis
Emotions
Chinese languages
Prosody
Second language learning
Sentiment analysis
Linguistics
Context
Comparative linguistics
Attitudes
Contrastive analysis
Semantics
Translation
English for Special Purposes
Negative Attitudes
Sentences
Novels
Essays
Contrastive Linguistics
Eskimo Aleut Languages
Social Media
Language Processing
Computational Linguistics
Algorithms
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Resumen:Traditional studies of semantic prosody, often relying on manual observation of limited concordance lines, face constraints such as small scale, susceptibility to subjective judgment, and difficulties in capturing emotional nuances in broader contexts. This study introduces sentiment analysis to conduct a contrastive investigation of semantic prosody in English and Chinese, with a focus on adverbs expressing completeness. The findings reveal that the specific context or "span" of text significantly influences the observed polarity strength of semantic prosody. Sentiment analysis incorporating contextual and syntactic factors yields more precise and nuanced results. Differences in semantic prosody between translational equivalents in the two languages reflect disparities in lexicalization patterns: English employs a wider range of adverbs to convey subtle emotional distinctions, while Chinese relies on more generalized terms with broader semantic ranges and an overall positive tendency. This research demonstrates the potential of computational methods in semantic prosody and contrastive linguistics, offering an efficient and scalable approach to data-driven analysis.
ISSN:2575-7938
2575-7946
DOI:10.26855/er.2025.09.004
Fuente:Education Database