Social Media in English and Russian Language Consciousness. Article 1. Psycholinguistic experiments

被引:2
作者
Shlyakhova, Svetlana [1 ]
Klyuev, Nikita [2 ]
机构
[1] Perm Natl Res Polytech Univ, Chair Foreign Languages & Publ Relat, 29 Komsomolsky Prospect, Perm 614990, Russia
[2] Perm Natl Res Polytech Univ, 29 Komsomolsky Prospect, Perm 614990, Russia
来源
PSYCHOLINGUISTICS | 2020年 / 27卷 / 02期
关键词
social media; social networks; psycholinguistics; 2.0; language consciousness; psycholinguistic experiment; English; Russian; INTERNET; TWITTER;
D O I
10.31470/2309-1797-2020-27-2-385-416
中图分类号
H0 [语言学];
学科分类号
030303 ; 0501 ; 050102 ;
摘要
Introduction. This research is devoted to the systematic description of a concept "social media" in the Russian and English linguistic consciousness. The article consists of two parts. The first part is dedicated to the research of the concept in a serial psycholinguistic experiment. The second part includes the analysis of the concept's presence in text corpora and also the field and the classificational cognitive models of the concept. The first part describes nominative fields of the concept "social media" and its subconcepts and provides a cognitive interpretation and a comparative analysis of the data in Russian and English languages. Methods of the research. The structure of the concept "social media" is set by the method of subjective definition of the word. The structure of subconcepts (social network, Facebook, Instagram, etc.) is set by the method of free associations. The procedure of cognitive interpretation sets cognitive classifiers of the concept. The significance of the quantitative analysis was diagnosed by the Fisher angular transformation method (criterion f). Results. The non-specific trait of the concept "social media" in Russian and English discourses is the identical classificational cognitive structure. Dissimilarities in the structure are noticeable only in the peripheral zones. The diffusion of the reactions (in various experiments) in the core and peripheral zones shows that the concept "social media" is socially and culturally specific. Conclusion. The results can be useful in the development of psycholinguistics 2.0, sociolinguistics, computational linguistics (OCR, ASR, data mining, automatic translation, etc.), lexicography, etc.
引用
收藏
页码:385 / 416
页数:32
相关论文
共 23 条
  • [1] Impact of the Internet Using Experience on the Peculiarities of the Internet Texts Understanding
    Akimova, Nataliia
    Oleksandrenko, Kateryna
    [J]. PSYCHOLINGUISTICS, 2019, 26 (01): : 11 - 36
  • [2] [Anonymous], 2017, P IEEE ACM INT C ADV, DOI DOI 10.1145/3110025.3110090
  • [3] Babenko M., 2018, KONCEPTOSFERA RUSSKO
  • [4] Exposure to opposing views on social media can increase political polarization
    Bail, Christopher A.
    Argyle, Lisa P.
    Brown, Taylor W.
    Bumpus, John P.
    Chen, Haohan
    Hunzaker, M. B. Fallin
    Lee, Jaemin
    Mann, Marcus
    Merhout, Friedolin
    Volfovsky, Alexander
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2018, 115 (37) : 9216 - 9221
  • [5] Representativeness of Social Media in Great Britain: Investigating Facebook, LinkedIn, Twitter, Pinterest, Google plus , and Instagram
    Blank, Grant
    Lutz, Christoph
    [J]. AMERICAN BEHAVIORAL SCIENTIST, 2017, 61 (07) : 741 - 756
  • [6] Detecting Automation of Twitter Accounts: Are You a Human, Bot, or Cyborg?
    Chu, Zi
    Gianvecchio, Steven
    Wang, Haining
    Jajodia, Sushil
    [J]. IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 2012, 9 (06) : 811 - 824
  • [7] Stweeler: A Framework for Twitter Bot Analysis
    Gilani, Zafar
    Wang, Liang
    Crowcroft, Jon
    Almeida, Mario
    Farahbakhsh, Reza
    [J]. PROCEEDINGS OF THE 25TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB (WWW'16 COMPANION), 2016, : 37 - 38
  • [8] Goroshko O., 2019, PSYKHOLINHVISTYKA, V26, P27, DOI [10.31470/2309-1797-2019-26-2-27-45, DOI 10.31470/2309-1797-2019-26-2-27-45]
  • [9] Changing Perspectives: Is It Sufficient to Detect Social Bots?
    Grimme, Christian
    Assenmacher, Dennis
    Adam, Lena
    [J]. SOCIAL COMPUTING AND SOCIAL MEDIA: USER EXPERIENCE AND BEHAVIOR, SCSM 2018, PT I, 2018, 10913 : 445 - 461
  • [10] Guo L, 2009, KDD-09: 15TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, P369