Methods of monitoring anglicisms in discourse of the Russian youth

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Abstract

The lack of long-term comprehensive monitoring of English borrowings in youth discourse and sociolect makes this study relevant. Our aim is to describe the authors’ methods for the qualitative and quantitative analysis of anglicisms in the sociolect of the Russian youth. We also aim to clarify the lexicographic consolidation modes of anglicisms in the Russian literary language. The hypothesis is that anglicisms dominate other linguistic units in the youth sociolect, such as newspeak and individual word creation. However, they do not entrench in the Russian literary language. This survey is a pilot macroproject, which encompasses two microprojects. The first microproject was conducted at Volgograd State University (2017-2019) and Saratov State University (2020-2022). The experiments involved 135 respondents aged 16 to 25. The second microproject was carried out at Kazan State University in 2022-2024. There were 210 respondents aged 15 to 25. The research material included 345 online and offline questionnaires and data from lexicographic sources and corpora. A unified methodology included classification and comparative methods, sociolinguistic interviewing, and psycholinguistic introspection. We have found out the main sources of English borrowings in the youth discourse and anglicisms frequency among slangisms. The influence of social characteristics on language variants distribution has been detected. The current findings demonstrate discrepancies between the indicators of anglicisms in the questionnaires and in the Russian National Corpus. The authors’ monitoring methods can be further applied for sovereignty preservation of the Russian language system.

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Table 1
The sample of a questionnaire

Word

Frequency use (0–5)

Social sphere of word use

The circumstances (place)  in which this word is used

Parents

Friends

Home

University

Internet

TV

Everyday commu-nication

Fuckingshit

0

–

–

–

–

–

–

–

Fan

4

–

+

–

+

-

+

+

Faraday

0

–

–

–

–

–

–

–

Fast

4

–

+

+

+

+

–

+

Fafakat’

1

–

–

–

+

–

–

+

Fake

4

–

+

–

+

+

–

+

Fail

2

–

+

+

+

+

–

+

Festivalit’

1

–

–

+

+

+

–

–

Figase

5

+

+

+

+

–

–

+

Bullshit

5

+

+

+

+

+

+

+

Filki

1

–

+

–

+

–

+

–

Babysit Philip

0

–

–

–

–

–

–

–

Filonit’

4

+

+

+

+

+

–

+

Fildepers

0

–

–

–

–

–

–

–

Filter

3

+

+

–

–

+

–

+

Fishka

3

+

+

–

+

+

–

+

Flash card

4

+

+

+

+

+

+

+

Follow

3

–

+

–

+

+

+

+

Trout

1

+

+

–

+

–

–

+

Fraer

3

–

+

–

+

+

–

+

Source: The data was calculated by A.A. Petrova based on the research corpus collected by the authors.

Fig. 1. Frequency use of the words from Table 1 presented in the pie chart
Source: the data was calculated by A.A. Petrova based on the research corpus.

Fig. 2. Data on the frequency of the anglicism «фаст» per million wordforms (by date)
Source: was designed by A.A. Petrova with the help of the programs of the RNC online dictionary, which is presented there on the page of this English-language borrowing. Retrieved July 10, 2024 from https://ruscorpora.ru/word/main?req=Фаст&seed=4288854320849368&gr=S

Fig. 3. Data on the frequency of the anglicism «фейк» per million wordforms (by date) 
Source: was designed by A.A. Petrova with the help of the programs of the RNC online dictionary,  which is presented there on the page of this English-language borrowing. Retrieved July 11, 2024 from https://ruscorpora.ru/word/main?req=Фейк&seed=4591192237756750&gr=S

Fig. 4. Data on the frequency of the anglicism «фанат» per million wordforms (by date)
Source: The graph was designed by A.A. Petrova with the help of the programs of the RNC online  dictionary, which is presented there on the page of this English-language borrowing. Retrieved July 15, 2024 from https://ruscorpora.ru/word/main?req=Фанат&seed=6990963670287246&gr=S

Fig. 5. Lexical-semantic field of the word «фанат»
Source: The figure was designed by the Neuro-SubCorpus of the Russian National Corpus. Retrieved July 15, 2024 from https://ruscorpora.ru/word/main?req=Фанат&seed=6990963670287246&gr=S

Fig. 6. Data on the frequency of the anglicism «флешка» per million wordforms (by date)
Source: was designed by A.A. Petrova with the help of the programs of the RNC online dictionary,  which is presented there on the page of this English-language borrowing. Retrieved July 15, 2024 from https://ruscorpora.ru/word/main?req=Флешка&seed=2926826865493596&gr=S

Table 2
Average frequency of the words from Questionnaire No. 2

Respondents‘ word ratings on Likert scale

Total Sum

YAD (poison) – 0,0,0,4,0,0,0,3,4,2,0,5,1,0,5

YALTO – 0,4,3,4,0,0,0,0,0,0,0,0,0,0,0,0

YANDEXIT’ – 5,5,1,3,1,5,5,5,0,0,0,0,0,0,0

YANIX– 5,2,0,0,0,0,0,0,0,0,0,0,0,0,0

YAP – 4,5,5,5,5,0,0,0,0,0,0,0,0,0,0

YABLOCHNIK – 1,3,4,2,5,0,0,0,0,0,0,0,0,0

YAOI – 3,1,5,5,4,2,0,0,0,0,0,0,0,0,0

LIKE – 4,3,3,2,5,5,5,5,5,5,5,5,5,5,5

LIFEHACK – 2,1,2,4,5,5,5,4,5,3,3,5,5,5,4

LAMPOVY – 1,2,5,5,1,4,3,4,4,5,0,0,0,0

LOSER – 5,4,5,2,5,5,2,5,5,5,2,1,1,5,1

LAGAT’ – 5,1,5,3,2,4,2,2,1,5,5,5,5,5,2

LULUM – 2,3,0,0,0,0,0,0,0,0,0,0,0,0,0

LOL – 5,5,1,5,2,4,5,5,5,5,5,0,5,5,5

LURKAT’ – 4,3,1,1,1,5,3,0,0,0,0,0,0,0,0

LINK – 1,2,1,5,0,1,5,2,1,0,1,0,0,0,0

LAITOVY – 4,2,1,3,0,3,2,5,4,0,2,3,0,0,0

LUKAS – 1,3,4,0,0,0,0,0,0,0,0,0,0,0,0

LUTSK – 3,3,3,0,0,0,0,0,0,0,0,0,0,0,0

LUBLU – 2,1,4,0,0,0,0,0,0,0,0,0,0,0,0

1,6

0,7

2,0

0,4

1,6

1,0

1,3

4,5

3,9

2,3

3,5

3,5

0,3

4,1

1,2

1,3

1,9

0,5

0,6

0,5

Source: The data from the authors’ research corpus was calculated by A.A. Petrova.

Fig. 7. Frequency of use of the words from Questionnaire № 2
Source: The bar-chart based on the data from the authors’ research corpus  was designed by A.A. Petrova.

Fig. 8. Data on the frequency of the anglicism «лайк» per million wordforms (by date)
Source: The graph was designed by A.A. Petrova with the help of the programs of the RNC online dictionary, which is presented there on the page of this English-language borrowing. Retrieved July 13, 2024 from https://ruscorpora.ru/word/main?req=лайк&seed=7772769277335506&gr=S

Fig. 9. Data on the frequency of the anglicism «лайфхак» per million wordforms (by date)
Source: The graph was designed by A.A. Petrova with the help of the programs of the RNC online dictionary, which is presented there on the page of this English-language borrowing. Retrieved July 12, 2024 from https://ruscorpora.ru/word/main?req=лайфхак&seed=8200276994492540&gr=S

 

Fig. 10. The most popular anglicisms
Source: The graph was compiled by I.V. Privalova based on the material collected  as a result of the survey of a targeted group of informants.

Table 3
Number of occurrences of a lemma in a specific subcorpus of the RNC

Number

Lemma

SubCorpus of the Russian  National Corpus

Frequency

Multimedia

From 2 to 15

Social Networks

Social Networks

Main

Corpus, imp

1.

Repost

 

 

62962

0,039

0,056

2.

Look

110

 

23304

0,014

1,076

3.

Go

 

94

20705

0,014

2,743

4.

Content

8

 

5705

0,003

1,912

5.

LOL

 

1

3160

0,002

0,032

6.

Usat’

1

 

1321

0,002

0,109

7.

Spoiler

4

 

1284

0,002

0,283

8.

Blogger

1

 

1220

0,002

0,104

9.

Bombit’

85

8

1030

0,002

4,612

10.

Sweatshirt

 

 

615

0,001

0,000

11.

Hype

1

 

598

0,001

0,048

12.

Toxic

 

 

207

0,001

0,000

13.

Flexit’

 

 

103

0,001

0,048/0,000

14.

Skill

 

 

84

0,001

0,000

15.

Fake

1

 

79

0,001

0,093

16.

Abuser

 

 

67

0,001

0,000

17.

Bulling

1

 

67

0,001

0,034

18.

Tishka

9

 

63

0,001

2,777

(noun, animate, masc)

19.

Trouble

 

 

41

0,001

0,053

20.

Bipolyarka

 

 

29

0,000

0,000

Source: The calculations were made by I.V. Privalova based on the author’s  research corpus.

×

About the authors

Irina V. Privalova

Kazan (Volga Region) Federal University

Author for correspondence.
Email: ivprivalova@mail.ru
ORCID iD: 0000-0002-7740-2185
SPIN-code: 9909-6839

Doctor of Philology, Associate Professor, Senior Researcher, Research Laboratory “Text Analytics”

18 Kremlevskaya St, Kazan, 420008, Russian Federation

Anna A. Petrova

Kazan (Volga Region) Federal University

Email: petrova16@mail.ru
ORCID iD: 0000-0003-4322-1324
SPIN-code: 7184-4466

Doctor of Philology, Associate Professor, Senior Researcher, Research Laboratory “Text Analytics”

18 Kremlevskaya St, Kazan, 420008, Russian Federation

Luiza N. Gishkaeva

RUDN University

Email: gishkaeva-ln@rudn.ru
ORCID iD: 0000-0001-7627-5375
SPIN-code: 8611-5700

PhD, Associate Professor of the Foreign Language Department, Faculty of Philology

6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation

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Supplementary files

Supplementary Files
Action
1. Fig. 1. Frequency use of the words from Table 1 presented in the pie chart
Source: the data was calculated by A.A. Petrova based on the research corpus.

Download (132KB)
Indexing metadata
2. Fig. 2. Data on the frequency of the anglicism «фаст» per million wordforms (by date)
S o u r c e : was designed by A.A. Petrova with the help of the programs of the RNC online dictionary, which is presented there on the page of this English-language borrowing. Retrieved July 10, 2024 from https://ruscorpora.ru/word/main?req=Фаст&seed=4288854320849368&gr=S

Download (68KB)
Indexing metadata
3. Fig. 3. Data on the frequency of the anglicism «фейк» per million wordforms (by date)
Source: was designed by A.A. Petrova with the help of the programs of the RNC online dictionary, which is presented there on the page of this English-language borrowing. Retrieved July 11, 2024 from https://ruscorpora.ru/word/main?req=Фейк&seed=4591192237756750&gr=S

Download (55KB)
Indexing metadata
4. Fig. 4. Data on the frequency of the anglicism «фанат» per million wordforms (by date)
Source: The graph was designed by A.A. Petrova with the help of the programs of the RNC online dictionary, which is presented there on the page of this English-language borrowing. Retrieved July 15, 2024 from https://ruscorpora.ru/word/main?req=Фанат&seed=6990963670287246&gr=S

Download (73KB)
Indexing metadata
5. Fig. 5. Lexical-semantic field of the word «фанат»
Source: The figure was designed by the Neuro-SubCorpus of the Russian National Corpus. Retrieved July 15, 2024 from https://ruscorpora.ru/word/main?req=Фанат&seed=6990963670287246&gr=S

Download (35KB)
Indexing metadata
6. Fig. 6. Data on the frequency of the anglicism «флешка» per million wordforms (by date)
Source: was designed by A.A. Petrova with the help of the programs of the RNC online dictionary, which is presented there on the page of this English-language borrowing. Retrieved July 15, 2024 from https://ruscorpora.ru/word/main?req=Флешка&seed=2926826865493596&gr=S

Download (55KB)
Indexing metadata
7. Fig. 7. Frequency of use of the words from Questionnaire № 2
Source: The bar-chart based on the data from the authors’ research corpus was designed by A.A. Petrova.

Download (128KB)
Indexing metadata
8. Fig. 9. Data on the frequency of the anglicism «лайфхак» per million wordforms (by date)
Source: The graph was designed by A.A. Petrova with the help of the programs of the RNC online dictionary, which is presented there on the page of this English-language borrowing. Retrieved July 12, 2024 from https://ruscorpora.ru/word/main?req=лайфхак&seed=8200276994492540&gr=S

Download (31KB)
Indexing metadata
9. Fig. 10. The most popular anglicisms
Source: The graph was compiled by I.V. Privalova based on the material collected as a result of the survey of a targeted group of informants.

Download (104KB)
Indexing metadata

Copyright (c) 2024 Privalova I.V., Petrova A.A., Gishkaeva L.N.

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