Psycholinguistics, Corpus Linguistics, and Text Analytics: Potential for Interaction
https://doi.org/10.26907/2541-7738.2023.3.43-54
Abstract
This article explores the possibilities of interaction between psycholinguistics, corpus linguistics, and text mining. When it comes to big data processing, the recent advances in psycholinguistics must be taken into account. In our digital reality, we should no longer view text as a mere sum of individual language units that are assembled based on their similarities in meaning. The insights of psycholinguistics into text have been revised, as in-depth text analysis unravels the new roles of the sender and the recipient, bringing to the fore qualitative methods for processing large data arrays. Without studying the mechanisms of speech generation and perception, it is impossible to improve language neural networks and machine translation engines. Here, the potential of psycholinguistics for training specialists in text analytics is discussed. As an example, the advantages of integrating the disciplines “Psycholinguistics” and “Psycholinguistic Methods for Studying Language and Text” into the psychological and linguistic module of the Master’s program “Text Analytics in Education and Science”, which has been launched at Kazan Federal University (Russia), are shown. The psycholinguistic component of the discipline “Corpus Linguistics” for Master’s students is described.
References
1. Biktimirov A.R., Gruzdev D.Yu. Boosting speech-to-text software potential. Nauchnyi Rezul’tat. Voprosy Teoreticheskoi i Prikladnoi Lingvistiki, 2022, vol. 8, no. 4, pp. 72–89. URL: https://doi.org/10.18413/2313-8912-2022-8-4-0-6. (In Russian)
2. Friginal E. Corpus Linguistics for English Teachers. Tools, Online Resources, and Classroom Activities. New York, Abingdon, Routledge, 2018. 366 p. URL: https://doi.org/10.4324/9781315649054.
3. Pérez-Paredes P. Corpus Linguistics for Education. A Guide for Research. New York, Routledge, 2020. 194 p. URL: https://doi.org/10.4324/9780429243615.
4. Timmis I. Corpus Linguistics for ELT. Research and Practice. Abingdon, New York, Routledge, 2015. 230 p. URL: https://doi.org/10.4324/9781315715537.
5. Jones Ch., Waller D. Corpus Linguistics for Grammar. A Guide for Research. Abingdon, N.Y., Routledge, 2015. 218 p. URL: https://doi.org/10.4324/9781315713779.
6. Semino E., Short M. Corpus Stylistics. Speech, Writing and Thought Presentation in a Corpus of English Writing. London, New York, Routledge, 2011. xii, 256 p. URL: https://doi.org/10.4324/9780203494073.
7. Szudarski P. Corpus Linguistics for Vocabulary. A Guide for Research. New York, Routledge, 2017. 238 p. URL: https://doi.org/10.4324/9781315107769.
8. Friginal E., Hardy J. Corpus-Based Sociolinguistics. A Guide for Students. New York, Abingdon, Routledge, 2014. 328 p. URL: https://doi.org/10.21283/2376905X.2.32.
9. Han C. Statistics in Corpus Linguistics: A Practical Guide, by Valclav Brezina, Cambridge, Cambridge University Press, 2018, xix+296 pp., ISBN: 978-1107565241. Journal of Quantitative Linguistics, 2020, vol. 27, no. 4, pp. 379–383. URL: https://doi.org/10.1080/09296174.2019.1646069.
10. Oakes M. Statistics for Corpus Linguistics. Ser.: Edinburgh Textbooks in Empirical Linguistics. Edinburgh, Edinburgh Univ. Press, 1998. 287 p. URL: https://doi.org/10.1515/9781474471381.
11. Gries S.Th. Quantitative Corpus Linguistics with R. A Practical Introduction. New York, Routledge, 2016. 286 p. URL: https://doi.org/10.4324/9781315746210.
12. Brezina V. Statistics in Corpus Linguistics: A Practical Guide. Cambridge, Cambridge Univ. Press, 2018. xx, 296 p. URL: https://doi.org/10.1017/9781316410899.
13. Wallis S. Statistics in Corpus Linguistics Research: A New Approach. New York, Abingdon, Routledge, 2021. 382 p. URL: https://doi.org/10.4324/9780429491696.
14. Svenja A., Carter R. Spoken Corpus Linguistics. From Monomodal to Multimodal. New York, Abingdon, Routledge, 2013. 216 p. URL: https://doi.org/10.4324/9780203526149.
15. Bauer L. Watching English Change: An Introduction to the Study of Linguistic Change in Standard Englishes in the Twentieth Century. London, Longman, 1994. 200 p.
16. Gorobets E.A., Mamontova A.V. Algorithm of automatic search for non-standard vocabulary units when creating a comprehensive dictionary. Aktual’nye Problemy Filologii i Pedagogicheskoi Lingvistiki, 2021, no. 2, pp. 131–142. URL: https://doi.org/10.29025/2079-6021-2022-2-131-142. (In Russian)
17. Borisov A.V. Current solutions and approaches to processing arrays of unstructured textual data in the field of big data. Problemy Sovremennoi Nauki i Obrazovaniya, 2017, no. 1 (83), pp. 49–52. (In Russian)
18. Popazova O.A., Shikhova N.N. Personnel management based on big data analytics: Risks and opportunities. Izvestiya SPbGEU, 2019, no. 3 (117), pp. 110–115. (In Russian)
19. Mizyukov G.S. Main approaches to processing large arrays of unstructured and quasi-structured textual data. Trudy Rostovskogo Gosudarstvennogo Universiteta Putei Soobshcheniya, 2017, no. 2, pp. 41–44. (In Russian)
20. Mashechkin I.V., Petrovskii M.I., Pospelova I.I., Tsarev D.V. Automatic summarization and keywords extraction methods for discovering extremist information on the Internet. Sovremennye Informatsionnye Tekhnologii i IT-Obrazovanie, 2016, vol. 12, no. 1, pp. 188–198. (In Russian)
21. Voicy speech analytics software. State Software Registration Certificate no. 2019667520, Dec. 24, 2019. Application no. 2019666394, Dec. 12, 2019. (In Russian)
22. Goncharovsky I.A., Polozov V.A. IQInScript speech analytics software. State Software Registration Certificate no. 2021667213, Nov. 26, 2021. Application no. 2021666043, Nov. 14, 2021. (In Russian)
23. Piotrovskaya K.R. Text analytics packages and computer linguodidactics. In: Aktual’nye problemy teoreticheskoi i prikladnoi lingvistiki i optimizatsiya prepodavaniya inostrannykh yazykov. K 80-letiyu professora L.I. Kornilovoi: sbornik materialov [Urgent Problems of Theoretical and Applied Linguistics and Optimization of Teaching Foreign Languages. On the 80th Anniversary of the Birthday of Professor L.I. Kornilova: A Collection of Articles], 2018, pp. 111–117. (In Russian)
24. Az-zari Kh.M., Anastas’ev A.N. Optimum Peresvet Analytics system for collecting and analyzing large arrays of data. State Software Registration Certificate no. 2018665392, Dec. 4, 2018. Application no. 2018661634, Nov. 24, 2018. (In Russian)
25. Karaulov Yu.N., Sorokin Yu.A., Tarasov E.F., Ufimtseva N.V., Cherkasova G.A. Russkii assotsiativnyi slovar’ [Russian Associative Dictionary]. Moscow, 1994. Associative Thesaurus of the Contemporary Russian Language, Russian Academy of Sciences, Russian Language Institute. URL: http://tesaurus.ru/dict/. (In Russian)
26. SIBAS – Russian Regional Associative Database (Siberia and Russian Far East), 2008–2020. URL: http://adictru.nsu.ru/. (In Russian)
27. Privalova I., Kazachkova M. Review of Sean Wallis. 2021. Statistics in Corpus Linguistics: A New Approach. New York, Oxon, Routledge. ISBN 9781138589384 ISBN 9780429491696 (eBook). Russian Journal of Linguistics, 2022, vol. 26, no. 2, pp. 550–557. URL: https://doi.org/10.22363/2687-0088-30209.
28. Privalova I.V. Methods of psycholinguistic research as possible cognitive approaches to linguistic data processing. In: Sukhova, N.V., Dubrovskaya, T., Lobina, Y.A. (Eds) Multimodality, Digitalization and Cognitivity in Communication and Pedagogy. Book Ser.: Numanities – Arts and Humanities in Progress. Vol. 20. Cham, Switzerland, Springer, 2021, pp. 181–201. URL: https://doi.org/10.1007/978-3-030-84071-6_11.
Review
For citations:
Privalova I.V. Psycholinguistics, Corpus Linguistics, and Text Analytics: Potential for Interaction. Uchenye Zapiski Kazanskogo Universiteta Seriya Gumanitarnye Nauki. 2023;165(3):43-54. (In Russ.) https://doi.org/10.26907/2541-7738.2023.3.43-54
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