Static Polycode Text Modeling Using Network Analysis (Demotivator Dedicated to Problems of Self-Isolation)

Abstract

The features of modeling a graphic-verbal polycode text, including a static image and an accompanying inscription, are considered. The study was conducted on the example of a demotivator dedicated to the problems of mass self-isolation at the very beginning of the pandemic and the introduction of restrictive measures. Significant semantic components, represented as part of only the iconic component, only the verbal component, and also as part of the verbal and iconic components at the same time are established. The semantic relations between the selected semantic components are revealed, the types of these links, revealing the different nature of their correlation are determined. On the basis of the data obtained, a network model of the considered static polycode text in the form of a semantic network was built. Cases of semantic components correlation are considered, reflecting the generally objective aspects of the situation and unrealistic ideas based on irony and hyperbole to create a comic effect. Based on quantitative analysis, representative semantic relations were established: “partitive”, “localization (in)”, “attributive”, “subject-object”. Non-representative semantic relations between the semantic components in the analyzed polycode text are revealed: “coincidence”, “localization (on)”, “temporal”, “subject-instrument”, “subject-result”.