Stereotypical Representation of a Female Politician in the Language Consciousness of Twitter Users

Author:

Tovkes M. Yu.1ORCID

Affiliation:

1. HSE University

Abstract

The study focuses on issues related to gender stereotypes of the blog community based on bloggers’ individual reactions and their impact on the perception of female politicians. The sample comprises tweets of the Russian- and English-speaking segments of this microblog, selected by keywords (based on the researcher’s view on the component structure of the thematic group «women in politics» and the representativeness of the sample) and collected with the help of the Python programming language. The classification of female politicians’ characteristics significant for users is made on the basis of feminine-masculine and psychophysiological criteria (according to E. G. Bakhteeva’s classification). The distribution of characteristics attributed to a female politician allows the researcher to determine which characteristics help women to fulfil their potential in politics or, on the contrary, hinder a successful political career. The results are interpreted in two aspects. On the one hand, from the point of view of the quantitative representation (percentage of characteristic groups), the field structure of the gender stereotype is compiled. On the other hand, in terms of qualitative indicator (content of characteristic’s groups, connotative components), the correlation of characteristics is identified and their visualization is performed with the help of Gephi software. As a result, the study builds models of a female-politician’s stereotypical image in the Russian- and English-speaking segments of Twitter and carries out their their comparative analysis. According to the first type of model, personal characteristics that may be inherent in both men and women are important for Russian- and English-speaking Twitter users, while typical masculine characteristics are the least relevant. For Russian-speaking users, high moral qualities are particularly relevant, while English-speaking bloggers appreciate high professional qualities. The graphs demonstrate that the language consciousness of the blog community tends to masculinize the stereotypical image of a female politician. Thus, a contradiction arises: bloggers explicitly acclaim the equal right for both men and women to fulfill their potential in politics, they recognize and accept the fact that women can be successful in the highest political positions and establishments and approve of the activity of particular women politicians. At the same time, traditional gender stereotypes, claiming that politics is a male sphere, implicitly retain their influence.

Publisher

Novosibirsk State University (NSU)

Reference32 articles.

1. Aivazova S. G. Gendernyi rakurs massovoi politiki // Zhenshchina v rossiiskom obshchestve. 2016. № 1 (78). S. 24-32.

2. Alyunina Yu. M. Blog kak istochnik noveishikh anglitsizmov: na materiale tekstov internet-diskursa mody // Vestnik NGU. Seriya: Lingvistika i mezhkul'turnaya kommunikatsiya. 2019. T. 17, № 4. S. 78-91.

3. Balakina Yu. V. Elektronnyi tekst: printsipial'no novyi tip teksta? // Vestnik Volgograd. gos. un-ta. Seriya 2: Yazykoznanie. 2016. T. 15, № 3. S. 17-27.

4. Bakhteeva E. G. Perspektivy transformatsii obraza zhenshchiny-politika v obshchestvennom soznanii rossiyan (na primere oprosov zhitelei g. Saratova i g. Moskvy, 2011 g.) // Izv. Saratov. un-ta. Novaya seriya. Seriya sotsiologiya. Politologiya. 2015. T. 15, vyp. 1. S. 100-104.

5. Bodalev A. A., Kunitsyna V. N., Panferova V. N. O sotsial'nykh etalonakh i stereotipakh i ikh roli v otsenke lichnosti // Chelovek i obshchestvo (Uchen. zap. NIIKSI). L.: Izd-vo LGU, 1971. Vyp. 9. S. 151-156.

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