“Chatbot Communication” as an Object of Linguistic Research in the System of Digital Communications - S. V. Kiseleva; A. A. Smirnova; N. A. Trofimova (Дискурс, 2022)
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.