NEUROCOGNITIVE DECODING AND SEMANTIC POLYSEMY OF IDEOGRAPHIC MARKERS IN DIGITAL DISCOURSE: A CONTRASTIVE ANALYSIS

This extended thesis introduces a novel cognitive-interpretive model to evaluate the semantic polysemy and conceptual decoding of ideographic markers (emojis) within modern computer-mediated communication (CMC). Departing from standard politeness taxonomies, this inquiry explores the semiotic evolution of visual markers from iconicity to abstract symbolic units within English and Uzbek digital discourse. By analyzing an empirical corpus of 2,800 naturally occurring interactional instances across multi-tier digital platforms (Telegram, Reddit, Discord, and X), the study examines how visual units modulate sentence-level semantic processing and cognitive load. Applying Conceptual Integration Theory and frame semantics, the research demonstrates that visual markers operate as dynamic semantic triggers that alter sentence interpretation through conceptual domain shifting. Furthermore, the paper proposes an algorithmic framework for integrating visual polysemy into low-resource computational models for Turkic Natural Language Processing (NLP).