Revisiting the grammaticalization of future be going to: A corpus-based approach

Through the quantification of frequency, existing corpus-based quantitative studies on grammaticalization offer a new direction for empirical investigation. However, most existing studies focus on general frequencies, failing to elucidate the relationship between frequency and grammaticalization. The proposition of critical frequency can reveal the relationship between frequency and grammaticalization and confirm the "threshold" that triggers grammaticalization. The present study explores the critical frequency (i.e., synchronic intensity and diachronic thickness) of future be going to and clarifies the relationship between its critical frequency and general frequency based on the corpora of EEBO, Google Books and COCA. The corpora are large enough for tracing the development of the fully grammaticalized be going to. Furthermore, the results retrieved from them can be mutually verified, thereby ensuring the validity of the present study. Quantitative analyses, including Chi-square test and linear regression test, are performed on the retrieved results. The findings include: (1) the diachronic thickness of future be going to lasts for 110 years (i.e., 1580-1690) and the synchronic intensity amounts to 0.81 per million words; (2) The critical frequency and the general frequency of future be going to are closely correlated. The present study confirms the threshold for triggering the grammaticalization of future be going to and elucidates the relationship between its critical frequency and general frequency. This study provides insights for future quantitative research on grammaticalization.

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Journal
PLoS ONE
Published
2026-07-24
DOI
https://doi.org/10.1371/journal.pone.0352674
Primary Topic
Syntax, Semantics, Linguistic Variation
Type
article
Field-Weighted Citation Impact
0.00

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article

Revisiting the grammaticalization of future be going to: A corpus-based approach

Junhui Wu, Zerui Dai
PLoS ONE
Syntax, Semantics, Linguistic Variation
article

Revisiting the grammaticalization of future be going to: A corpus-based approach

Junhui Wu, Zerui Dai
article en

Abstract

Through the quantification of frequency, existing corpus-based quantitative studies on grammaticalization offer a new direction for empirical investigation. However, most existing studies focus on general frequencies, failing to elucidate the relationship between frequency and grammaticalization. The proposition of critical frequency can reveal the relationship between frequency and grammaticalization and confirm the "threshold" that triggers grammaticalization. The present study explores the critical frequency (i.e., synchronic intensity and diachronic thickness) of future be going to and clarifies the relationship between its critical frequency and general frequency based on the corpora of EEBO, Google Books and COCA. The corpora are large enough for tracing the development of the fully grammaticalized be going to. Furthermore, the results retrieved from them can be mutually verified, thereby ensuring the validity of the present study. Quantitative analyses, including Chi-square test and linear regression test, are performed on the retrieved results. The findings include: (1) the diachronic thickness of future be going to lasts for 110 years (i.e., 1580-1690) and the synchronic intensity amounts to 0.81 per million words; (2) The critical frequency and the general frequency of future be going to are closely correlated. The present study confirms the threshold for triggering the grammaticalization of future be going to and elucidates the relationship between its critical frequency and general frequency. This study provides insights for future quantitative research on grammaticalization.

PLoS ONEVol. 21(7)
Changsha University of Science and Technology (CN)
Philosophy and Social Science Foundation of Hunan Province
Quality Education
Openalex Percentile: Top 2%
Syntax, Semantics, Linguistic Variation
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Revisiting the grammaticalization of future be going to: A corpus-based approach — Junhui Wu, Zerui Dai · PLoS ONE (2026) | TGRS Research Map | TGRS