“Chatbot Communication” as an Object of Linguistic Research in the System of Digital Communications

Introduction. The authors of the article consider one of the interesting technologies in the digitalization segment – a chatbot – from a linguistic point of view. The topic is of particular interest to linguists, since the active development of the digital environment leads to the emergence of new means and forms of speech production and speech perception, with their own distinctive features, patterns and rules of construction. Speech acts in the Internet discourse system within the framework of this work are of key importance: the object of study is located at the intersection of several disciplines (IT, Advertising and PR), but from a linguistic point of view it is practically not considered.

Methodology and sources. To clarify some theoretical inaccuracies in the scientific work, corpus analysis of the texts of English-language and Russian-language web corpus is used. English-language web corpus: “NOW corpus” (News on the Web), “iWeb corpus”, “GloWbE corpus” (Global Web-based English). Russian-language web corpora: “ruTenTen2011” and GIKRYA. The analysis of the features of the construction of speech acts in chatbot communication is carried out on the basis of the language material of English and Russian chatbots in various social networks and instant messengers.

Results and discussion. Corpus text analysis helps to consider the object of study from a linguistic point of view and supplement existing knowledge with linguistic data. The analysis of empirical material based on two languages allows us to compare, identify the characteristics of chatbot communication texts, trace similarities and differences in the cognitive perception of speech, and also find errors in the construction of speech acts.

Conclusion. Systematization of data and a more detailed analysis of such a concept as “chatbot communication” will help in the future to create universal linguistic-cognitive models for bots with a final scenario, which will help to avoid mistakes and make the communication act as successful as possible. Chatbots, from the point of view of the communicative function, when organizing speech acts, must use special rules and linguistic models in order to bring the speech act to success. Just as self-learning bots in the category of artificial intelligence are created with the active participation of linguists, so chatbots in social networks and instant messengers must be subject to uniform linguistic laws.

1. “Global Digital 2022: annual report on the Internet and social networks – the main figures”, (2022), Sostav.ru, available at: https://www.sostav.ru/publication/we-are-social-i-hootsuite-52472.html (accessed 28.01.2022).

2. Crystal, D. (2011), Internet Linguistics: A Student Guide, Routledge, NY, USA.

3. Arutyunova, N.D. (1999), Yazyk i mir cheloveka Language and the human world, Yazyki russkoi kul'tury, Moscow, RUS.

4. Teun, A. van Dijk (2008), Discourse and Context A Sociocognitive Approach, Cambridge Univ. Press, Cambridge, UK, available at: http://www.cambridge.org/9780521895590 (accessed 10.12.2021).

5. Karasik, V.I. (2004), Yazykovoi krug: lichnost', kontsepty, diskurs Language circle: personality, concepts, discourse, Gnosis, Moscow, RUS.

6. Bohlen, E. (2021), “Chatbots: what is it”, SAS, available at: https://www.sas.com/ru_ru/insights/articles/analytics/what-are-chatbots.html (accessed 10.12.2021).

7. Krivonosov, A.D., Filatova, O.G. and Shishkina, M.A. (2018), Osnovy teorii svyazei s obshchestvennost'yu Fundamentals of the theory of public relations, 2nd ed., Peter, SPb., RUS.

8. Jacobson, R. (1975), Lingvistika i poetika Linguistics and poetics, available at: http://philologos.narod.ru/classics/jakobson-lp.htm (accessed 29.09.2021).

9. Bakhtin, M.M. (1986), Estetika slovesnogo tvorchestva Aesthetics of verbal creativity, Iskusstvo, Moscow, USSR.

10. Нуmеs, D.Н. (1975), “The Ethnography of Speaking”, Transl. from English, Novoe v lingvistike. Vyp. VII. Sotsiolingvistika New in linguistics, iss. VII. Sociolinguistics, Progress, Moscow, USSR, pp. 42–95.

11. Austin, J. (1999), “How To Do Things With Words”, Favorites, Transl. by Makeeva, L.B. and Rudnev, V.P., Ideya-Press, Dom intellektual'noi knigi, Moscow, RUS, pp. 13–136.

12. Searle, J. (1965), “What is a speech act?”, Philosophy in America, Black, M. (ed.), Alien and Unwin, London, UK, pp. 221–239.

13. Grice, H.P. (1957), “Meaning“, Philosophical Review, vol. 66, no. 3, pp. 377–388. DOI: https://doi.org/10.2307/2182440.

14. Karasik, V.I. (2019), “Genres of network discourse”, Speech Genres, no. 1 (21), pp. 49–55. DOI: https://doi.org/10.18500/2311-0740-2019-1-21-49-55.

15. Gal'perin, I.R. (2006), Tekst kak ob"ekt lingvisticheskogo issledovaniya Text as an object of linguistic research, Nauka, Moscow, RUS.

16. Latipova, A.L. (2018), “Linguistic features of the language of the Internet discourse”, Ivzestia of the Volgograd State Pedagogical Univ., no. 6 (129), pp. 159–163.

17. Maslikova, O.S. (2019), “Linguistic features of communication in the Internet space”, Innovation science, no. 9, pp. 69–72.

18. Chepurnykh, V.I. (1988), “On the communicative-pragmatic approach to the study of graphic stylistic means in a literary text”, Semantika i pragmatika edinits yazyka v tekste: mezhvuz. sb. nauch. tr. Semantics and pragmatics of language units in the text: interuniver. collection of scientific papers, in Guchinskaya, I.O. et al. (eds.), LGPI im. A.I. Gertsena, Leningrad, USSR, pp. 147–153.

19. “Programmer's Library: Chatbots: developer's introduction” (2017), Proglib.io, available at: https://proglib.io/p/chat-bots-intro/amp/ (accessed 20.11.2021).

20. Zakharov, V.P. (2003), “Internet search engines as a tool for linguistic research”, Russkii yazyk v Internete: sb. st. Russian language on the Internet: sat. articles, Otechestvo, Kazan', RUS, pp. 48–59.

21. Raiskina, V.A. and Dubnyakova, O.A. (2015), “Modern methods of corpus linguistics in text analysis (on the example of the BFM corpus)”, Aktual'nye voprosy sovremennoi nauki Actual problems of modern science, no. 40, pp. 146–154.

22. Kochetova, L.A. and Kononova, I.V. (2019), “A cognitive corpus approach to the study of construing values in advertising discourse”, Issues of cognitive linguistics, no. 2, pp. 65–74.

23. “Corpus of English texts”, (2022), English-Corpora, available at: https://www.englishcorpora.org/ (accessed 20.01.2022).

24. “Corpus “Russian web 2011””, (2022), Sketch Engine, available at: https://www.sketchengine.eu/ (accessed 20.01.2022).

25. General Internet Corpus of the Russian Language”, (2022), GIKRYA, available at: http://www.webcorpora.ru/ (accessed 20.01.2022).

26. “Results of the year: fakes, neural networks and the victory of the Internet” (2016), Gazeta.ru, available at: https://www.gazeta.ru/tech/2016/12/20_a_10439129.shtml (accessed 01.12.2021).

27. “Chatbot Paganel” (2012), Zateiniki, available at: https://zatejnik.ucoz.ru/news/podelis_svoej_mechtoj_s_paganelkoj/2012-04-24-20 (accessed 01.02.2022).

28. Kodachigov, V. (2011), “LJ is losing its audience”, Vedomosti, available at: https://www.vedomosti.ru/technology/articles/2011/10/12/poluzhivoj_zhurnal (accessed 20.01.2022).

29. “HealthTap chat bot in Telegram” (2021), Telegram.org, available at: https://web.telegram.org/#/im?p=@ghealthtap_bot (accessed 20.10.2021).

30. “Chatbot MTS in Vkontakte” (2021), Vkontakte.ru, available at: https://vk.com/im?sel=-8458649 (accessed 01.08.2021).