Signal or Noise? Readability and Signaling in the First Year of IFRS S2 Sustainability Reporting in an Emerging Market: Evidence from Türkiye

This study examines the first corporate disclosures issued under the IFRS Sustainability Standards, with full alignment to IFRS S2, using natural language processing and text mining techniques, and contributes evidence to an underexplored phase of sustainability reporting research. Focusing on an emerging market setting, the analysis covers the 2024 reports of 18 firms included in the Borsa Istanbul Sustainability 25 Index. The reports are evaluated through readability metrics (Flesch–Kincaid, Gunning Fog, and SMOG), conceptual concentration measures (TF–IDF), semantic proximity analysis (Cosine Similarity), and network-based methods. The findings indicate a strong degree of technical discipline and standard adherence in the first year of implementation, alongside a pronounced barrier to linguistic accessibility. Average Gunning Fog and Flesch–Kincaid scores of 18.94 and 14.90 suggest that meaningful interpretation of these disclosures requires advanced academic proficiency. The observed technical density reflects the detailed and standard-driven structure of IFRS-based sustainability reporting and points to a persistent tension between technical precision and interpretability, consistent with the Managerial Obfuscation perspective (H1). High levels of semantic overlap further indicate that, under conditions of reporting uncertainty, firms rely heavily on established disclosure patterns, reinforcing professional convergence through both coercive (regulatory alignment) and mimetic (uncertainty-driven emulation) isomorphism (H2). In contrast, distinct narrative configurations identified through principal component and network analyses are evaluated as potential credibility-enhancing signals within the framework of Signaling Theory (H3). Overall, IFRS Sustainability Standards reporting functions in emerging markets as a learning-oriented and strategically relevant disclosure mechanism that may potentially mitigate information asymmetry through its linguistic properties.