Get on with and Continue with: Similarity Analysis

Authors

  • Namkil Kang

    College of Liberal Arts, Far East University, 76-32 Daehak-gil, Gamgok-myeon, Eumseong-gun, Chungbuk 27737, Republic of Korea
  • Hyewon Cho

    College of Liberal Arts, Far East University, 76-32 Daehak-gil, Gamgok-myeon, Eumseong-gun, Chungbuk 27737, Republic of Korea

DOI:

https://doi.org/10.30564/fls.v7i4.8764
Received: 16 February 2025 | Revised: 15 March 2025 | Accepted: 21 March 2025 | Published Online: 30 March 2025

Abstract

This article provides an in-depth similarity analysis of the phrases get on with and continue with using data from the Corpus of Contemporary American English (COCA), the British National Corpus (BNC), and ChatGPT. A key finding is that in COCA, the two phrases share a 33.33% similarity in ranking analysis, whereas in BNC, their similarity is 0%. In COCA, get on with is most similar to continue with in the newspaper genre and least similar in TV/movies. Conversely, in BNC, their closest similarity occurs in magazines and their greatest divergence in fiction. Standard deviation analysis further highlights differences in frequency. In COCA, get on with has a standard deviation of 294.02, indicating a frequency range of 199.48 to 787.52, while continue with has a standard deviation of 194.4, with a range of 163.98 to 552.78. Although their frequency correlation is not statistically significant, COCA shows a weak positive correlation, while BNC reveals a weak negative correlation. Notably, in neither corpus does the frequency of get on with significantly affect continue with. Additionally, eight of their top 20 collocations overlap, reflecting a 40% similarity in usage. Overall, the findings suggest minimal similarity between these phrases, with clear distinctions between American and British English. These insights contribute to a deeper understanding of how phrase usage varies across different linguistic and cultural contexts.

Keywords:

Ranking; Euclidean Distance; Standard Deviation; Correlation; Linear Regression

References

[1] Corpus of Contemporary American English (COCA). Available from: https://corpus.byu.edu/coca (cited 17 January 2025).

[2] British National Corpus (BNC), 2025. Available from: https://corpus.byu.edu/bnc (cited 17 January 2025).

[3] ChatGPT. Available from: https://chat.openai.com (cited 17 January 2025).

[4] Hansard Corpus (HC). Available from: https://english-corpora.org/hansard/ (cited 17 January 2025).

[5] Corpus of Historical American English (COHA). Available from: https://corpus.byu.edu/coha (cited 17 January 2025).

[6] Murphy, R., 2016. Grammar in Use. Cambridge University Press: Cambridge, UK.

[7] Murphy, R., 2019. English Grammar in Use. Cambridge University Press: New York, NY, USA.

[8] Aarts, B., Granger, S., 1993. Corpus-based approaches to grammar. Benjamins Publishing: Amsterdam, The Netherlands.

[9] Barlow, M., Kuperman, V., 2008. Corpus linguistics: A guide to the theory and practice. Palgrave Macmillan: New York, NY, USA.

[10] Biber, D., 1993. Representativeness in corpus design. Literary and Linguistic Computing. 8(4), 243–257. DOI: https://doi.org/10.1093/llc/8.4.243

[11] Biber, D., Conrad, S., Reppen, R., 1998. Corpus linguistics: Investigating language structure and use. Cambridge University Press: Cambridge, UK.

[12] Channell, J., 2000. Corpus linguistics: A resource book for students. Routledge: London, UK.

[13] Casal, J.E., Shirai, Y., Lu, X., 2022. English verb-argument construction profiles in a specialized academic corpus: Variation by genre and discipline. English for Specific Purposes. 66, 94–107.

[14] Firth, J.R., 1957. Papers in linguistics 1934–1951. Oxford University Press: Oxford, UK.

[15] Gries, S.T., 2013. Statistics for linguists: A step-by-step guide. Mouton de Gruyter: Berlin, Germany.

[16] Hunston, S., Francis, G., 2000. Pattern grammar: A corpus-driven approach to the lexical grammar of English. John Benjamins Publishing: Amsterdam, The Netherlands.

[17] Kilgarriff, A., Grefenstette, G., 2003. Introduction to the special issue on corpus-based approaches to lexical semantics. Computational Linguistics. 29(4), 493–500. DOI: https://doi.org/10.1162/089120103322753347.​

[18] Kovaliuk, Y., 2023. Idioms in general English corpora: on frequency, register, and cross-variety variation. Respectus Philologicus. 44, 11–24.

[19] Leech, G., Fallon, P., 1992. Computer corpora and linguistic theory. Language. 68(3), 459–482. DOI: https://doi.org/10.2307/415793.​

[20] Marušić, B., 2023. Multi-word expressions in annual reports of American and British corporations: a corpus-based diachronic study. Journal of Teaching English for Specific and Academic Purposes. 793–811.

[21] Matsumoto, N., 2020. A genre-based analysis of evaluative modality in multi-verb sequences in English. In: Hohaus, P., Schulze, R. (eds.). Re-Assessing Modalising Expressions. John Benjamins Publishing Company: Amsterdam, The Netherlands. pp. 225–252.

[22] McEnery, T., Kawai, Y., 2008. Collocational patterning in English: A corpus-based study. Language and Computers. 63, 75–88.

[23] McEnery, T., Wilson, A., 2001. Corpus linguistics: An introduction. Edinburgh University Press: Edinburgh, UK.

[24] Meyer, C., 2002. English corpus linguistics: An introduction. Cambridge University Press: Cambridge, UK.

[25] O'Keeffe, A., McCarthy, M., Carter, R., 2007. From corpus to classroom: Language use and language teaching. Cambridge University Press: Cambridge, UK.

[26] Sinclair, J., 1991. Corpus, concordance, collocation. Oxford University Press: Oxford, UK.

[27] Tognini-Bonelli, R., 1993. Interpretative Nodes in Discourse — Actual and Actually. In: Baker, M., Francis, G., Tognini-Bonelli, E. (eds.). Text and Technology: In honour of John Sinclair. John Benjamins Publishing Company: Amsterdam, Netherlands. 193–212. DOI: https://doi.org/10.1075/z.64.13tog

[28] Wasserman, L., 2004. All of Statistics: A Concise Course in Statistical Inference. Springer: Berlin, Germany. DOI: https://doi.org/10.1007/978-0-387-21736-9

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How to Cite

Kang, N., & Cho, H. (2025). Get on with and Continue with: Similarity Analysis. Forum for Linguistic Studies, 7(4), 226–237. https://doi.org/10.30564/fls.v7i4.8764

Issue

Vol. 7 , Iss. 4 (April 2025): In Progress

Article Type

Article

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Copyright © 2025 Namkil Kang, Hyewon Cho

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This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.