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Title: Marking trustworthiness with near synonyms: a corpus-based study of “Renwei” and “Yiwei” in Chinese
Authors: Li, B 
Huang, CR 
Chen, S 
Issue Date: 2020
Source: In ML Nguyen, MC Luong & S Song (Eds.), Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation, 24-26 October, 2020, University of Science, Vietnam National University Hanoi, Vietnam, p. 453-461. Association for Computational Linguistics (ACL), 2020
Abstract: We conducted a corpus-based study on near synonymous cognitive verbs “renwei 認為” and “yiwei 以為” with a similar meaning of “to think” in Chinese. The motivation of this study is that information trustworthiness in propositions varies with the use of “renwei” or “yiwei”, which concerns the issue of speakers’ stances or attitudes. We examined the epistemic modality attributed to “renwei” and “yiwei” in written discourse, by testing their different functions of evidential marking, negative forms and hedging device. Results showed that “renwei” was associated with specialized and professional subjects and consequently demonstrated its relatively high degree of evidentiality. Then, specific negative polarity shifters exclusively collocating with “yiwei” denoted larger scope of negation of entire propositions. Lastly, only “renwei” functioned as a hedge to mitigate claims lacking full commitment in the political discourse. Therefore, the evidence of data proved that the epistemic marker “renwei” was associated with a higher degree of information trustworthiness, contributing to the annotation system in NLP for the detection of information credibility.
Keywords: Information trustworthiness
Near-synonyms
Epistemic modality
Publisher: Association for Computational Linguistics (ACL)
Rights: Copyright of contributed papers reserved by respective authors.
Posted with permission of the author.
The following publication Bei Li, Chu-Ren Huang, and Si Chen. 2020. Marking Trustworthiness with Near Synonyms: A Corpus-based Study of “Renwei” and “Yiwei” in Chinese. In Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation, pages 453–461, Hanoi, Vietnam. Association for Computational Linguistics is available at https://aclanthology.org/2020.paclic-1.52.
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