J. Dunn. Natural Language Processing for Corpus Linguistics. Cambridge University Press, 2022. 84 pp.

Reviewed by

Hanna Schmück | Lancaster University

Available under the Creative Commons Attribution (CC BY) 4.0 license.

For any use beyond this license, please contact the publisher at rights@benjamins.nl.

Open Access publication of this article was funded through a Transformative Agreement with Lancaster University.

Published online: 22 December 2023

https://doi.org/10.1075/ijcl.00057.sch

References (11)

References

Biber, D. (2012). Register as a predictor of linguistic variation. Corpus Linguistics and Linguistic Theory, 8(1), 9–37.

Djuric, P. M., & Miguez, J. (2009). Model assessment with Kolmogorov-Smirnov statistics. In IEEE International Conference on Acoustics, Speech, and Signal Processing (pp. 2973–2976). IEEE.

Dunn, J., & Adams, B. (2020). Geographically-balanced gigaword corpora for 50 language varieties. In N. Calzolari, F. Béchet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, & S. Piperidis (Eds.), Proceedings of the Twelfth Language Resources and Evaluation Conference (pp. 2528–2536). European Language Resources Association. [URL]

Garimella, A., Banea, C., Hovy, D., & Mihalcea, R. (2019). Women’s syntactic resilience and men’s grammatical luck: Gender-bias in part-of-speech tagging and dependency parsing. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. [URL].

Honkapohja, A., & Suomela, J. (2022). Lexical and function words or language and text type? Abbreviation consistency in an aligned corpus of Latin and Middle English plague tracts. Digital Scholarship in the Humanities, 37(3), 765–787.

Langacker, R. W. (2008). Cognitive Grammar: A Basic Introduction. Oxford University Press.

Mastropierro, L. (2017). Corpus Stylistics in Heart of Darkness and its Italian Translations. Bloomsbury Academic.

Nakamata, N. (2019). Vocabulary depends on topic, and so does grammar. Journal of Japanese Linguistics, 35(2), 213–234.

Powers, D. M. W. (2011). Evaluation: From precision, recall and F-measure to ROC, informedness, markedness and correlation. Journal of Machine Learning Technologies, 2(1), 37–63. [URL]

Vries, W. de, Wieling, M., & Nissim, M. (2022). Make the best of cross-lingual transfer: Evidence from POS Tagging with over 100 Languages. In S. Muresan, P. Nakov, & A. Villavicencio (Eds.), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Volume 1: Long Papers. Association for Computational Linguistics. [URL].

Wilson Black, J., Brand, J., Hay, J., & Clark, L. (2023). Using principal component analysis to explore co-variation of vowels. Language and Linguistics Compass, 17(1), Article e12479.

Cited by (1)

Cited by one other publication

Kopytina, N., E. Bocharova & L. Gulina

2024. NEW FINDINGS OF CULTURED MICROMYCETES IN THE DEEP-SEA SEDIMENTS OF THE BLACK SEA. Transactions of Papanin Institute for Biology of Inland Waters RAS ► pp. 45 ff.

This list is based on CrossRef data as of 12 december 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

J. Dunn. Natural Language Processing for Corpus Linguistics. Cambridge University Press, 2022. 84 pp.

Cited by one other publication

J. Dunn. Natural Language Processing for Corpus Linguistics. Cambridge University Press, 2022. 84 pp.