Startseite Evaluative language in Chinese online food discourse: overall distribution, local patterning, and readers’ involvement
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Evaluative language in Chinese online food discourse: overall distribution, local patterning, and readers’ involvement

  • Chan-Chia Hsu

    Chan-Chia Hsu received his Ph.D. in Linguistics from National Taiwan University and is currently an associate professor at the Center for General Education, National Taipei University of Business. His research interests include pragmatics, discourse analysis, lexical semantics, and corpus linguistics. His most recent publications and presentations are on Chinese multi-word expressions, evaluative stances, online discourse, and application of corpus linguistics to language learning and teaching.

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    , Yu-Yun Chang

    Yu-Yun Chang is an assistant professor at the Graduate Institute of Linguistics, National Chengchi University in Taiwan. Her research interests include corpus linguistics, semantics, pragmatics, and computational linguistics. She has a keen interest in research topics related to readers’ commitments and/or persuasion strategies. She seeks ways to implement linguistic knowledge in real-life applications, and has been working on a non-profit initiative to combat fake news.

    und Yun Biao

    Yun Biao is a master’s student at the Graduate Institute of Linguistics, National Chengchi University. Her research interest lies in the field of computational linguistics. Her most recent publication is related to persuasion strategies used in online crowdfunding platforms. Additionally, she is interested in topics related to sentiment analysis, particularly focusing on analyzing the emotions of song lyrics in Mandarin Chinese.

Veröffentlicht/Copyright: 30. September 2024

Abstract

Internet users often express their evaluation of food in online posts. This study sets out to comprehensively annotate evaluative words in food posts in Chinese, which deserves more attention due to its increasing dominance on the Internet. The corpus includes 180 posts from Dcard, currently the largest anonymous social media platform in Taiwan. All the words annotated to be evaluative are categorized according to their grammatical class, evaluative function, and subjective polarity. We not only provide the frequency distributions of the evaluative words but also conduct four case studies of high-frequency evaluative words, identifying their lexico-syntactic patterns. While previous studies on evaluative language have tended to focus on particular words/phrases, with the data mainly from English, the present study provides a more comprehensive quantitative perspective and extends to Chinese data. Moreover, because conveying evaluations in online forums can be a mediatized performance intended for attention and visibility, our qualitative analysis demonstrates how Dcard users establish readers’ involvement through evaluation.


Corresponding author: Chan-Chia Hsu, Center for General Education, National Taipei University of Business, No. 321, Sec. 1, Jinan Rd., Zhongzheng District, Taipei City, 10051, Taiwan, ROC, E-mail:

Award Identifier / Grant number: MOST111-2410-H-141-006-MY2

About the authors

Chan-Chia Hsu

Chan-Chia Hsu received his Ph.D. in Linguistics from National Taiwan University and is currently an associate professor at the Center for General Education, National Taipei University of Business. His research interests include pragmatics, discourse analysis, lexical semantics, and corpus linguistics. His most recent publications and presentations are on Chinese multi-word expressions, evaluative stances, online discourse, and application of corpus linguistics to language learning and teaching.

Yu-Yun Chang

Yu-Yun Chang is an assistant professor at the Graduate Institute of Linguistics, National Chengchi University in Taiwan. Her research interests include corpus linguistics, semantics, pragmatics, and computational linguistics. She has a keen interest in research topics related to readers’ commitments and/or persuasion strategies. She seeks ways to implement linguistic knowledge in real-life applications, and has been working on a non-profit initiative to combat fake news.

Yun Biao

Yun Biao is a master’s student at the Graduate Institute of Linguistics, National Chengchi University. Her research interest lies in the field of computational linguistics. Her most recent publication is related to persuasion strategies used in online crowdfunding platforms. Additionally, she is interested in topics related to sentiment analysis, particularly focusing on analyzing the emotions of song lyrics in Mandarin Chinese.

  1. Research funding: This work was supported by the National Science and Technology Council, formerly the Ministry of Science and Technology, in Taiwan, R.O.C. (grant number: MOST111-2410-H-141-006-MY2).

Appendix A: Results of the hierarchical configural frequency analysis of the relationship between the evaluative words’ grammatical category and evaluative function

Evaluative function Grammatical category Freq Exp Cont.chisq Obs-exp P.adj.bin Dec Q
Evaluation of other objects Verb 122 748.1487 524.0431 < 5.95E-194 *** 0.133
Indirect value judgment Adjective 41 482.1996 403.6857 < 1.44E-156 *** 0.089
Indirect value judgment Verb 496 149.9066 799.0351 > 1.84E-113 *** 0.065
Evaluation of other objects Adjective 3,115 2,406.545 208.5598 > 3.27E-81 *** 0.232
Attitude Verb 411 137.6451 542.8664 > 1.36E-80 *** 0.051
Attitude Adjective 215 442.7585 117.1608 < 2.19E-34 *** 0.045
Evaluation of other objects Adverb 43 171.1044 95.9107 < 4.96E-31 *** 0.024
Indirect value judgment Adverb 118 34.2842 204.4188 > 5.61E-28 *** 0.015
Manner Adverb 63 10.1315 275.88 > 8.43E-28 *** 0.01
Attitude Noun 18 65.3814 34.3369 < 6.67E-11 *** 0.009
Manner Noun 3 21.0423 15.47 < 2.53E-05 *** 0.003
Manner Adjective 103 142.497 10.9477 < 0.005340599 ** 0.007
Evaluation of other objects Noun 403 355.3706 6.3836 > 0.10990803 ns 0.009
Attitude Four 29 18.735 5.6242 > 0.329071822 ns 0.002
Indirect value judgment Noun 89 71.2056 4.4469 > 0.447890777 ns 0.003
Attitude Adverb 23 31.4799 2.2843 < 1.435565503 ns 0.002
Indirect value judgment Four 14 20.404 2.01 < 1.79462326 ns 0.001
Manner Verb 51 44.2996 1.0134 > 3.476512637 ns 0.001
Manner Four 4 6.0297 0.6832 < 5.619136522 ns 0
Evaluation of other objects Four 100 101.8313 0.0329 < 9.065749019 ns 0

Appendix B: Results of the hierarchical configural frequency analysis of the relationship between the evaluative words’ grammatical category and subjective polarity

Grammatical category Subjective polarity Freq Exp Cont.chisq Obs-exp P.adj.bin Dec Q
Verb Negative 115 152.082 9.0417 < 0.008864 ** 0.007
Four Negative 8 20.7001 7.7919 < 0.013198 * 0.002
Adjective Negative 549 489.1972 7.3107 > 0.028228 * 0.012
Noun Negative 54 72.239 4.605 < 0.147845 ns 0.003
Adjective Positive 2,925 2,984.803 1.1982 < 0.535517 ns 0.02
Verb Positive 965 927.918 1.4819 > 0.942094 ns 0.008
Adverb Negative 43 34.7817 1.9418 > 0.975314 ns 0.002
Four Positive 139 126.2999 1.2771 > 1.365741 ns 0.002
Noun Positive 459 440.761 0.7547 > 1.886608 ns 0.004
Adverb Positive 204 212.2183 0.3183 < 2.970941 ns 0.002

Appendix C: Results of the hierarchical configural frequency analysis of the relationship between the evaluative words’ evaluative function and subjective polarity

Evaluative function Subjective polarity Freq Exp Cont.chisq Obs-exp P.adj.bin Dec Q
Indirect value judgment Negative 64 106.7391 17.113 < 3.66E-05 *** 0.008
Attitude Negative 139 98.0084 17.1446 > 0.00038 *** 0.008
Attitude Positive 557 597.9916 2.8099 < 0.309004 ns 0.008
Indirect value judgment Positive 694 651.2609 2.8048 > 0.318515 ns 0.009
Manner Negative 33 31.5429 0.0673 > 3.36771 ns 0
Manner Positive 191 192.4571 0.011 < 3.812108 ns 0
Evaluation of other objects Negative 533 532.7096 2.00E-04 > 4.010975 ns 0
Evaluation of other objects Positive 3,250 3,250.29 0 < 4.015648 ns 0

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Received: 2023-08-25
Accepted: 2024-09-12
Published Online: 2024-09-30
Published in Print: 2025-07-28

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