Green promises and unverifiable claims: detecting corporate greenwashing in Indonesian sustainability reports through corpus linguistics and natural language processing - Arif Nugroho (CV Narasi Khatulistiwa Indonesia, 2026)
Background: Corporate sustainability reports increasingly combine ambitious environmental commitments with uneven evidence, creating difficulties in distinguishing accountable disclosure from potentially misleading green claims. Objective: This study examines how Indonesian corporations construct environmental responsibility and whether linguistic promises, documentary specification, and visual legitimation remain mutually aligned. Method: A comparative corpus-assisted design integrates rule-based natural language processing, claim-verifiability assessment, and multimodal coding across six official sustainability reports, thirty-six contextual passages, and six report covers from three corporations during 2023–2024. Results: Promissory language dominated the textual corpus, whereas quantified performance statements occurred less frequently and future-oriented markers extended across most coded passages. Documentary analysis classified most units as having low verifiability, with time boundaries appearing more often than baselines, operational scopes, or assurance references. Implication: Cover analysis revealed recurrent combinations of nature imagery, community actors, green colour salience, and corporate logos, producing strong visual narratives of ecological and social responsibility. Novelty: This study introduces an integrated diagnostic framework that conceptualises greenwashing risk as misalignment among linguistic projection, evidential completeness, and multimodal legitimacy rather than as a property of isolated positive words, numerical claims, or environmental images and enables transparent comparison across companies, reporting years, claim types, evidential attributes, and visual strategies while preserving cautious interpretive boundaries in corporate reporting.