UDC

81’33

DOI

10.37482/2687-1505-V206

Authors

Anastasiya V. Kolmogorova
National Research University Higher School of Economics; nab. kanala Griboedova 123, St. Petersburg, 190068, Russian Federation;
ORCID: https://orcid.org/0000-0002-6425-2050 e-mail: nastiakol@mail.ru
Alina V. Malikova
Siberian Federal University; prosp. Svobodnyy 82, str. 1, Krasnoyarsk, 660041, Russian Federation;
ORCID: https://orcid.org/0000-0002-3438-1839 e-mail: malikovaav1304@gmail.com

Abstract

This study was carried out in the field of emotional text analysis. The aim of the paper was statistical modelling of the emotional perception of Internet texts in the Russian language by Tuvan-Russian bilinguals. A hypothesis about the significance of the factor of mental lexicon organization in the emotional markup of texts by this group was tested. We assumed that, due to the complexity of the psycholinguistic reality of the bilingual linguistic consciousness of the Tuvans, the markup would reflect some specific features in their processing of emotional information expressed verbally in a non-native, but communicatively meaningful language. The research material included 48 texts from the dataset of posts from the social network VKontakte: 6 texts for each emotional class according to Lövheim’s three-dimensional model for emotions, i.e. distress, enjoyment, disgust, surprise, excitement, anger, shame, and fear. A computer interface developed and tested by the research group was used for non-discrete emotional markup of texts. The psycholinguistic experiment involved 174 Russian monolinguals and 65 Tuvan-Russian bilinguals. Before moving on to annotation, bilingual informants completed the Bilingual Language Profile questionnaire for us to obtain data on their dominant language. To analyse the results, we applied the Student’s t-test and the comparative method. We found a statistical significance of differences in the affective evaluations attributed to texts in the Russian language by Russian monolinguals and Tuvan-Russian bilinguals (the majority of them were 18–25 years old). According to the results, the magnitude of these differences depends on the bilingual’s dominant language. There is a discrepancy in secondary emotions between Russian monolinguals and Tuvan-Russian bilinguals, while the texts’ leading emotion is common for both groups. In addition, we observed a certain instability in bilinguals’ evaluations when they were asked to do the task again due to a technical error. The results of this research contribute to the study of bilinguals’ perception of emotions in texts.

Keywords

affective computing, bilingualism, dominant language, Internet text, psycholinguistics, Tuvan language, emotion analysis

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