Abstract:
This article is devoted to the representation of the method of a three-component analysis of Internet commentary. Commentary is a special component of Internet discourse which is the reaction of representatives of society to any external or internal stimulus expressed linguistically, i.e. through the use of linguistic means. Due to insufficient coverage (for example, unlike Internet posts), commentary as a component of political Internet discourse represents a wide field for the study of linguists since, being a speech work, it can be analyzed from at least three positions, namely: the strategy and tactics used by the author, the means of stylistic expressiveness used and the type of speech act through which this commentary is put into use. A comprehensive analysis of these parameters makes it possible to establish the attitude of the audience (in this case, the electorate) to the personality of Boris Johnson, the Prime Minister of Great Britain. Practical material for the study was the comments on the posts of Boris Johnson regarding Brexit (one of the key events in the political and public spheres of Great Britain’s life). The relevance of this work is due to the current anthropocentric paradigm in linguistics and the increased interest of linguists not only in humans as a participant of speech actions, but also in the interdisciplinary synthesis of scientific research methods to achieve the most voluminous, full-fledged, and complete results. The purpose of this article is to demonstrate an example of the implementation of the three-component analysis methodology for Internet commentary on the example of some of the most striking and connotatively colored linguistic materials selected by the method of continuous sampling in the social network “Twitter”.
Keywords: discourse, political Internet discourse, commentary, social network, linguopragmatic potential, strategy, tactics, Brexit, electorate, Twitter.
For citation: Katermina V.V., Vulfovich B.G. Methods of a Three-Component Analysis of Linguopragmatic Potential of an Internet Commentary in Political Internet Discourse. Current Issues in Philology and Pedagogical Linguistics. 2021, no 4, рр. 83–89 (In Russ.).
Bionote:
Veronika V. Katermina1*, Boris G. Vulfovich2
1, 2Kuban State University,
149 Stavropolskaya Str., Krasnodar, Russian Federation, 350040;
1ORCID ID: 0000-0001-9141-9867; Researcher ID: L-2817-2017;
Scopus Author ID: 5719404821
2ORCID ID: 0000-0002-7358-9819
*e-mail: katermina_v@mail.ru
References:
1. Katermina VV., Vulfovich BG. Linguopragmatic potential of political Internet discourse. Actual problems of philology and pedagogical linguistics. 2019, 2:19-26 (In Russ.).
2. Benvenist E. General Linguistics. Ed. Yu.S. Stepanova. M.: Progress, 1974; 446 (in Russ.).
3. Humboldt V. Selected Works on Linguistics. M.: Progress, 1984; 400 (In Russ).
4. Serio P. How to read texts in France. Square of meaning: French School of Discourse Analysis: Per. With Fr. and Portuga. M.: Progress, 1999; 12-53 (In Russ).
5. Anderson J. Public PolicyMaking: An Introduction. Boston, N.Y. 2003.
6. Lacatus C. Populism and President Trump’s Approach to Foreign Policy: An Analysis of Tweets and Rally Speeches Politics. Politics. 2020; 41 (1): 31-47. DOI: 10.1177 / 0263395720935380. W / s.
7. Van Dijk T. Discourse and Context: A Sociocognitive Approach. Cambridge: Cambridge University Press. 2006 (In Russ.).
8. Patyukova RV. Comparative analysis of the concepts of public and political communication. Bulletin of the Chelyabinsk State University. 2009; 34 (172): 67-72 (In Russ.).
9. Burghardt M. Introduction to Tools and Methods for the Analysis of Twitter Data. Living Linguistics. Media linguistics. 2015; 1: 74-91.
10. Crystal D. Language and the Internet. Cambridge: Cup, 2006.
11. Cunha E. Analyzing The Dynamic Evolution of Hashtags on Twitter: A Language-Based Approach. In Proceedings of the workshop on Language in Social Media LSM. 2011; 58-65.
12. Derczynski L. Twitter Part-of-Speech Tagging for All: Overcoming Sparse and Noisy Data. In Proceedings of the International Conference On Recent Advances in Natural Language Processing, ACL. 2013; 198-206.
13. Enli G. Twitter As Arena for the authentic Outsider: Exploring The Social Media Campaigns of Trump and Clinton In The 2016 US Presidential Election. European journal of communication. 2017; 32 (1): 50-61. DOI: https://doi.org/10/1177/0267323116682802.
14. González-Ibáñez R. Identifying Sarcasm in Twitter: A Closer Look. In HLT ‘11 Proceedings of the Association for Computational Linguistics: Human Language Technologies: Short Papers. 2011; 581-586.
15. Murthy D. Introduction to Social Media, Activism, and Organizations. Social Media + Society. 2018;1-4. DOI: 10.1177 / 2056305117750716.
16. Rees A. Digital and Online Activism. Available at: https://en.reset.org/knowledge/digital-and-online-activism. Access September 13, 2020 (In Russ.).
17. Zanzotto FM. Linguistic Redundancy in Twitter. In proc. of the 2011 Conference on Empirical Methods in Natural Language Processing, ACL, 2011; 659-669.
18. Issers OS. Communicative strategies and tactics of Russian speech. M.: Editorial URSS, 2003; 284 (In Russ.).
19. Ryabchenko NA., Katermina VV., Gnedash AA., Vulfovich BG. Regional Political Discourse: Theoretic Model, Methodology of Research and Practice of Managing Political Content In The Online Space of the Russian Federation Subjects. Political Linguistics. 2019; 5 (77): 114-131. DOI 10.26170 / PL19-05-12.
20. Karaulov YuN. Russian language and language identity. M.: Science, 1987; 264 (In Russ.).
21. Wodak R., Forchtner B. Introducing the Language-Politics Nexus. The Routledge Handbook of Language and Politics. Milton Park, Abingdon, Oxon; NEW YORK, NY: ROUTLEDGE. 2017; 1-14.