Correlating Sense Components in Memes and Demotivators About Mass Self-Isolation: Types of Semantic Relations

Abstract

The article is devoted to the study of semantic components correlation in the content of Russian memes and demotivators about mass self-isolation during the COVID-19 pandemic. The sampling consisted of 1,500 Russian memes and demotivators. The application of a network approach to the analysis of the sense structure of verbal-visual polycode texts has enabled the author to identify the cases of specific semantic components correlation, and describe the types of their semantic relations, including localization, identity, attribution, temporal correlation, opposition, cause-and-effect, subject, object and instrument. The research highlights the fact that the correlation of semantic components by means of a certain type of semantic relations can reflect both objective information, certain trends and patterns observed in society, and subjective ideas about mass self-isolation. The examples of comic effect emergence are described. The cases when the correlation between semantic components is expressed verbally (both semantic components are represented in the verbal part of the polycode text), non-verbally (both semantic components are represented in the iconic part of the polycode text), synsemantically (one of the correlating semantic components is expressed verbally, and the other is depicted iconically) are analyzed. It has been noted that representation form mainly depends on the specificity of the correlated semantic components in the polycode text, and the author's individual preferences. Explicitly and implicitly expressed links between certain semantic components in the analyzed polycode texts devoted to mass self-isolation are considered. The correlation of certain semantic components of polycode texts reveals the peculiarities of perception and understanding of various aspects of this phenomenon.