1887
Volume 29, Issue 1
  • ISSN 1384-6655
  • E-ISSN: 1569-9811
USD
Buy:$35.00 + Taxes

Abstract

Abstract

This paper reports a corpus-based, cognitive semantic study on profiling the varied uses of the Chinese color term “black” with regard to its metaphorical polysemy. We hypothesize that the semantic (dis)similarities among the eight metaphorical meanings of “black” can be captured by clustering their contextual features, including collocational patterns, morphosyntactic and semantic properties, and discourse information. The Behavioral Profiles approach is adopted for the analyses with the annotations of 800 instances for 46 contextual features and a hierarchical agglomerative cluster analysis conducted on the annotated data. The results show that the eight metaphorical senses of “black” fall into three clusters. This clustering can be explained by the conceptual bases pertaining to color perceptions and color changes, in line with Conceptual Metaphor Theory. This study demonstrates the effectiveness of the corpus-based Behavioral Profiles approach in exploring the underlying cognitive mechanisms of metaphorical extensions and meaning differentiations.

Loading

Article metrics loading...

/content/journals/10.1075/ijcl.21067.liu
2023-06-15
2025-02-13
Loading full text...

Full text loading...

References

  1. Aliakbari, M., & Khosravian, F.
    (2013) A corpus analysis of color-term conceptual metaphors in Persian proverbs. Procedia – Social and Behavioral Sciences, 701, 11–17. 10.1016/j.sbspro.2013.01.033
    https://doi.org/10.1016/j.sbspro.2013.01.033 [Google Scholar]
  2. Al-Jarf, R.
    (2019) Translation students’ difficulties with English and Arabic color-based metaphorical expressions. Fachsprache, 41(S1), 101–118. 10.24989/fs.v41iS1.1774
    https://doi.org/10.24989/fs.v41iS1.1774 [Google Scholar]
  3. Allan, K.
    (2009) The connotations of English color terms: Color-based X-phemisms. Journal of Pragmatics, 41(3), 626–637. 10.1016/j.pragma.2008.06.004
    https://doi.org/10.1016/j.pragma.2008.06.004 [Google Scholar]
  4. Altman, D. G.
    (1990) Practical Statistics for Medical Research. Chapman and Hall. 10.1201/9780429258589
    https://doi.org/10.1201/9780429258589 [Google Scholar]
  5. Amouzadeha, M., Tavangara, M., & Sorahia, M.
    (2011) A cognitive study of color terms in Persian and English. Proceeding of 4th International Conference of Cognitive Science (pp.238–245). Elsevier. 10.1016/j.sbspro.2012.01.035
    https://doi.org/10.1016/j.sbspro.2012.01.035 [Google Scholar]
  6. Apresjan, J.
    (1974) Regular polysemy. Linguistics, 12(142), 5–32. 10.1515/ling.1974.12.142.5
    https://doi.org/10.1515/ling.1974.12.142.5 [Google Scholar]
  7. Atkins, B. T. S.
    (1987) Semantic ID tags: Corpus evidence for dictionary senses. Proceedings of the Third Annual Conference of the UW Centre for the New Oxford English Dictionary (pp.17–36). University of Waterloo. https://www.degruyter.com/database/COGBIB/entry/cogbib.740/html
    [Google Scholar]
  8. Berlin, B., & Kay, P.
    (1969) Basic Color Terms: Their Universality and Evolution. University of California Press.
    [Google Scholar]
  9. Chatti, S.
    (2016) Translating colour metaphors: A cognitive perspective. InM. Taibi (Ed.), New Insights into Arabic Translation and Interpreting (pp.161–176). Channel View. 10.21832/9781783095254‑009
    https://doi.org/10.21832/9781783095254-009 [Google Scholar]
  10. Copestake, A., & Briscoe, T.
    (1995) Semi-productive polysemy and sense extension. Journal of Semantics, 12(1), 15–67. 10.1093/jos/12.1.15
    https://doi.org/10.1093/jos/12.1.15 [Google Scholar]
  11. Divjak, D.
    (2003) On trying in Russian: A tentative network model for near(er)-synonyms. Slavica Gandensia, 301, 25–58.
    [Google Scholar]
  12. (2010) Structuring the Lexicon: A Clustered Model for Near-synonymy. De Gruyter Mouton. 10.1515/9783110220599
    https://doi.org/10.1515/9783110220599 [Google Scholar]
  13. Divjak, D., & Gries, S. Th.
    (2009) Corpus-based cognitive semantics: A contrastive study of phasal verbs in English and Russian. InB. Lewandowska-Tomaszczyk & K. Dziwirek (Eds.), Studies in Cognitive Corpus Linguistics (pp.273–296). Peter Lang.
    [Google Scholar]
  14. (2006) Ways of trying in Russian: Clustering behavioral profiles. Corpus Linguistics and Linguistic Theory, 2(1), 23–60. 10.1515/CLLT.2006.002
    https://doi.org/10.1515/CLLT.2006.002 [Google Scholar]
  15. Dosedlová, A., & Lu, W. L.
    (2019) The near-synonymy of classifiers and construal operation: A corpus-based study of 棵 and 株 zhū in Chinese. Review of Cognitive Linguistics, 17(1), 113–130. 10.1075/rcl.00028.dos
    https://doi.org/10.1075/rcl.00028.dos [Google Scholar]
  16. Fillmore, C. J.
    (1985) Frames and the semantics of understanding. Quaderni di semantica, 6(2), 222–254.
    [Google Scholar]
  17. Firth, J.
    (1951) Modes of meaning. InF. R. Palmer (Ed.), Linguistics (pp.1934–1951). Oxford University Press.
    [Google Scholar]
  18. Ghafel, B., & Mirzaie, A.
    (2014) Colors in everyday metaphoric language of Persian speakers. Procedia – Social and Behavioral Sciences, 1361, 133–143. 10.1016/j.sbspro.2014.05.303
    https://doi.org/10.1016/j.sbspro.2014.05.303 [Google Scholar]
  19. Gower, J. C.
    (1971) A general coefficient of similarity and some of its properties. Biometrics, 27(4), 857–874. 10.2307/2528823
    https://doi.org/10.2307/2528823 [Google Scholar]
  20. Gries, S. Th.
    (2006) Corpus-based methods and cognitive semantics: The many senses of to run. InS. Th. Gries & A. Stefanowitsch (Eds.), Corpora in Cognitive Linguistics: Corpus-Based Approaches to Syntax and Lexis (pp.57–99). De Gruyter Mouton. 10.1515/9783110197709.57
    https://doi.org/10.1515/9783110197709.57 [Google Scholar]
  21. (2017) Ten Lectures on Quantitative Approaches in Cognitive Linguistics. Brill. 10.1163/9789004336223
    https://doi.org/10.1163/9789004336223 [Google Scholar]
  22. Gries, S. Th., & Divjak, D.
    (2009) Behavioral profiles: A corpus-based approach to cognitive semantic analysis. InV. Evans & S. Pourcel (Eds.), New Directions in Cognitive Linguistics (pp.57–75). John Benjamins. 10.1075/hcp.24.07gri
    https://doi.org/10.1075/hcp.24.07gri [Google Scholar]
  23. Hanks, P.
    (1996) Contextual dependency and lexical sets. International Journal of Corpus Linguistics, 1(1), 75–98. 10.1075/ijcl.1.1.06han
    https://doi.org/10.1075/ijcl.1.1.06han [Google Scholar]
  24. Harris, Z. S.
    (1954) Distributional structure. Word, 10(2–3), 146–162. 10.1080/00437956.1954.11659520
    https://doi.org/10.1080/00437956.1954.11659520 [Google Scholar]
  25. Hastürkoğlu, G.
    (2018) Incorporation of conceptual metaphor theory in translation pedagogy: A case study on translating simile-based idioms. Australian Journal of Linguistics, 38(4), 467–483. 10.1080/07268602.2018.1510728
    https://doi.org/10.1080/07268602.2018.1510728 [Google Scholar]
  26. Hill, P.
    (2008) The metaphorical use of colour terms in the Slavonic languages. InD. N. Wells (Ed.), Themes and Variations in Slavic Languages and Cultures (pp.62–83). Australia and New Zealand Slavists’ Association.
    [Google Scholar]
  27. Institute of Linguistics, Chinese Academy of Social Sciences
    Institute of Linguistics, Chinese Academy of Social Sciences (2016) hēi 黑 “black”. InThe Contemporary Chinese Dictionary (7th ed., p.531). The Commercial Press.
    [Google Scholar]
  28. Ioannou, G.
    (2020) Image schemas as prototypes in the diachronic evolution of kámnō and eutheiázō in Greek: A behavioural-profile analysis. Lingua, 2451, 1–32. 10.1016/j.lingua.2020.102938
    https://doi.org/10.1016/j.lingua.2020.102938 [Google Scholar]
  29. Jackendoff, R.
    (2002) Foundations of Language. Oxford University Press. 10.1093/acprof:oso/9780198270126.001.0001
    https://doi.org/10.1093/acprof:oso/9780198270126.001.0001 [Google Scholar]
  30. Jansegers, M., & Gries, S. Th.
    (2017) Towards a dynamic behavioral profile: A diachronic study of polysemous sentir in Spanish. Corpus Linguistics and Linguistic Theory, 16(1), 145–187. 10.1515/cllt‑2016‑0080
    https://doi.org/10.1515/cllt-2016-0080 [Google Scholar]
  31. Jansegers, M., Vanderschueren, C., & Enghels, R.
    (2015) The polysemy of the Spanish verb sentir: A behavioral profile analysis. Cognitive Linguistics, 26(3), 381–421. 10.1515/cog‑2014‑0055
    https://doi.org/10.1515/cog-2014-0055 [Google Scholar]
  32. Jurafsky, D.
    (1996) Universal tendencies in the semantics of the diminutive. Language, 72(3), 533–578. 10.2307/416278
    https://doi.org/10.2307/416278 [Google Scholar]
  33. Kilgarriff, A., & Tugwell, D.
    (2001) Word sketch: Extraction and display of significant collocations for lexicography. Information Technology Research Institute Technical Report Series. University of Brighton.
    [Google Scholar]
  34. Kilgarriff, A., Baisa, V., Bušta, J., Jakubíček, M., Kovář, V., Michelfeit, J., Rychlý, P., & Suchomel, V.
    (2014) The Sketch Engine: Ten years on. Lexicography, 1(1), 7–36. 10.1007/s40607‑014‑0009‑9
    https://doi.org/10.1007/s40607-014-0009-9 [Google Scholar]
  35. Klepousniotou, E.
    (2002) The processing of lexical ambiguity: Homonymy and polysemy in the mental lexicon. Brain and Language, 81(1–3), 205–223. 10.1006/brln.2001.2518
    https://doi.org/10.1006/brln.2001.2518 [Google Scholar]
  36. Kruskal, J. B.
    (1964) Multidimensional Scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrica, 29(1), 1–27. 10.1007/BF02289565
    https://doi.org/10.1007/BF02289565 [Google Scholar]
  37. Lai, H. L., & Chung, S. F.
    (2018) Color polysemy: Black and white in Taiwanese language. Taiwan Journal of Linguistics, 16(1), 95–130.
    [Google Scholar]
  38. Lakoff, G.
    (1987) Women, Fire, and Dangerous Things: What Categories Reveal About the Mind. The University of Chicago Press. 10.7208/chicago/9780226471013.001.0001
    https://doi.org/10.7208/chicago/9780226471013.001.0001 [Google Scholar]
  39. Lakoff, G., & Johnson, M.
    (1980) Metaphors We Live By. University of Chicago Press.
    [Google Scholar]
  40. Lakoff, G.
    (1993) The contemporary theory of metaphor. InA. Ortony (Ed.), Metaphor and Thought (pp.202–251). Cambridge University Press. 10.1017/CBO9781139173865.013
    https://doi.org/10.1017/CBO9781139173865.013 [Google Scholar]
  41. Landis, J. R., & Koch, G. G.
    (1977) The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. 10.2307/2529310
    https://doi.org/10.2307/2529310 [Google Scholar]
  42. Levshina, N.
    (2011) Doe wat je niet laten kan: A Usage-based Analysis of Dutch Causative Constructions [Doctoral dissertation, University of Leuven]. University of Leuven.
    [Google Scholar]
  43. Li, Z. C., & Bai, H. R.
    (2013) Conceptual metaphors of black and white: A corpus-based comparative study between English and Chinese. Journal of Anhui Agricultural University (Social Science Edition), 22(4), 92–97.
    [Google Scholar]
  44. Liesenfeld, A., Liu, M. C., & Huang, C. R.
    (2022) Profiling the Chinese causative construction with rang (讓), shi (使) and ling (令) using frame semantic features. Corpus Linguistics and Linguistic Theory, 18(2), 263–306. 10.1515/cllt‑2020‑0027
    https://doi.org/10.1515/cllt-2020-0027 [Google Scholar]
  45. Liu, D.
    (2010) Is it a chief, main, major, primary, or principal concern: A corpus-based behavioral profile study of the near-synonyms. International Journal of Corpus Linguistics, 15(1), 56–87. 10.1075/ijcl.15.1.03liu
    https://doi.org/10.1075/ijcl.15.1.03liu [Google Scholar]
  46. McHugh, M. L.
    (2012) Interrater reliability: The kappa statistic. Biochemia Medica, 22(3), 276–282. 10.11613/BM.2012.031
    https://doi.org/10.11613/BM.2012.031 [Google Scholar]
  47. Murphy, G.
    (2002) The Big Book of Concepts. MIT Press. 10.7551/mitpress/1602.001.0001
    https://doi.org/10.7551/mitpress/1602.001.0001 [Google Scholar]
  48. Pustejovsky, J.
    (1995) The Generative Lexicon. MIT Press.
    [Google Scholar]
  49. R Core Team
    R Core Team (2021) R: A language and environment for statistical computing (Version 4.1.1) [Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/
    [Google Scholar]
  50. Suzuki, R., Terada, Y., & Shimodaira, H.
    (2019) pvclust: Hierarchical Clustering with P-Values via Multiscale Bootstrap Resampling (R package version 2.2-0) [Computer software]. https://CRAN.R-project.org/package=pvclust
  51. Wierzbicka, A.
    (1990) The meaning of color terms: Semantic, culture and cognition. Cognitive Linguistics, 1(1), 99–150. 10.1515/cogl.1990.1.1.99
    https://doi.org/10.1515/cogl.1990.1.1.99 [Google Scholar]
  52. Wu, J. S.
    (2011) The evolution of basic color terms in Chinese. Journal of Chinese Linguistics, 39(1), 76–122.
    [Google Scholar]
  53. Wu, T. P.
    (1986) 论颜色词及其模糊性质 [Analysis on color terms and their fuzzy nature]. Language Teaching and Linguistic Studies, 21, 88–105.
    [Google Scholar]
  54. Xing, Z. Q.
    (2008) Semantics and pragmatics of color terms in Chinese. InZ. Q. Xing (Ed.), Studies of Chinese Linguistics: Functional Approaches (pp.87–102). Hong Kong University Press.
    [Google Scholar]
  55. Xu, Y., Malt, B. C., & Srinivasan, M.
    (2017) Evolution of word meanings through metaphorical mapping: Systematicity over the past millennium. Cognitive Psychology, 961, 41–53. 10.1016/j.cogpsych.2017.05.005
    https://doi.org/10.1016/j.cogpsych.2017.05.005 [Google Scholar]
  56. Zhang, W. X.
    (1988) 色彩词语联想意义初论 [Analysis on the associative meanings of color terms]. Language Teaching and Linguistic Studies, 31, 112–121.
    [Google Scholar]
/content/journals/10.1075/ijcl.21067.liu
Loading
/content/journals/10.1075/ijcl.21067.liu
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error