Applying Chi-Square Test In Measuring The Significance Of The Occurrence Of French Synonym In Corpus Data

  • Weddha Savitri Udayana University
  • Ni Luh Sutjiati Beratha Udayana University
  • I Nengah Sudipa Udayana University
  • I Made Rajeg Udayana University
Keywords: Adjective, French, Chi-Square, Corpus Data, Near-Synonym, Synonymy

Abstract

This paper explains how to apply the significance test of a synonym set in French to its appearance in a data corpus. The chi-square significance test is a procedure that can be used to test the significance of quantitative data statistically. The object of this research is a series of adjective synonyms with the core meaning 'extraordinary' in French. This research uses Leipzig corpora collection as data source, and AntConc (version 4.2.0) as a tool used in searching for the frequency of occurrence of each synonymous word in the news and website data corpus. The results of the significance test show that distributions differences between the real frequency of occurrence and the expected frequency of occurrence of synonymous words in the data corpus can be considered as not just a coincidence. With a p value < 0.001, it can be concluded that there is a significant relationship between the differences in the distribution of each adjective in different types of data corpus

References

Biber, Douglas, Susan Conrad and Randi Reppen. (1998). Corpus Linguistics: Investigating Languagestructure and use. Cambridge: Cambridge University Press.

Cruse, D. Alan. (2006). Meaning in Language: An Introduction into Semantiks and Pragmatic. Oxford University Press.

D. Goldhahn, T. Eckart & U. (2012). Quasthoff: Building Large Monolingual Dictionaries at the Leipzig Corpora Collection: From 100 to 200 Languages. In: Proceedings of the 8th International Language Resources and Evaluation (LREC'12)

Dixon, R.M.W. (2010). Basic Linguistic Theory: Volume 2 Gramatical Topics. New York: Oxford University Press

Gries, S. T. (2013). Statistics for linguistics with R: A practica introduction (2nd ed.). Berlin: Mouton de Gruyter

Facchinetti, R. (2007). Corpus Linguistisc 25 Years On. Amsterdam – New York: Rodopi

Inkpen, D. & Hirst, G. (2002). Building and using a lexical knowledge base of near synonym differences. Computational Lingusitics. 32(2), 223-262

Levshina, N. (2015). How to do Linguistics with R: Data exploration and statistical analysis. John Benjamins Publishing Company

Lyons, J. (1968). Introduction to Theoretical Linguistics. Cambridge University Press, Cambridge.

Moon, R. (2010). What can a corpus tells us about lexis? In: A O’Keffe and M. McCarthy (Eds). The Routledges handbook of corpus linguistics. (pp.197-211). Oxford: Routledge

Palmer, F. R. (1981). Semantics. London: Cambridge University Press

Rajeg, G. P. W., & Rajeg, I. M. (2019). Pemahaman Kuantitatif Dasar Dan Penerapannya Dalam Mengkaji Keterkaitan Antara Bentuk Dan Makna. Linguistik Indonesia, 37(1), 13–31. https://doi.org/10.26499/li.v37i1.87

Rajeg, G. P. W. (2020). Linguistik Korpus Kuantitatif Dan Kajian Semantik Leksikal Sinonim Emosi Bahasa Indonesia. Linguistik Indonesia, 38(2)

Sinclair, J. (1991). Corpus, Concordance, Collocation: Describing English language. Oxford: Oxford University Press.

Stefanowitsch, A. (2010). Empirical cognitive semantics: Some thoughts. In Dylan Glynn & Kerstin Fischer (Eds.), Quantitative methods in cognitive semantics: Corpus-driven approaches (pp. 355–380). Berlin: Mouton de Gruyter

https://synonyms-fr.com

https://synonyms-fr.com

https://corpora.uni-leipzig.de/

Published
2024-09-16