Prototype Development of a Python-Based Application for Allegory Detection in Electronic News Coverage

Abstract

Allegory represents an extended figurative construction in which narrative elements—characters, actions, events, and symbolic structures—encode meanings beyond their literal level. In electronic news reporting, allegory may be used to simplify complex issues, frame institutional identity, and convey ideological nuances through symbolic narratives. This study aims to develop a Python-based prototype capable of detecting allegorical expressions in electronic news texts and analyzing their discursive implications through a Critical Discourse Analysis (CDA) perspective. The research integrates text preprocessing, narrative pattern recognition, symbolic cue extraction, and lexical-semantic analysis to identify indicators of allegorical structures. The corpus consists of online news articles related to institutional coverage published between 2020–2025. The CDA framework, particularly Fairclough’s three-dimensional model, is employed to interpret the ideological and discursive functions of allegory. The prototype demonstrates preliminary accuracy in detecting allegorical patterns, particularly narrative sequences that portray institutions metaphorically as agents, guardians, vessels, or journeys. Findings indicate that allegory functions not merely as a stylistic device but as a discursive strategy to construct institutional identity, reinforce legitimacy, and shape public perception. The study contributes theoretically to discourse linguistics and figurative language analysis, and practically by providing a computational tool for identifying allegory in news media.