Sentiment Analysis of Sustainability Disclosures in the Tech Sector: An AI-Based Assessment of Environmental Accountability
Sentiment Analysis of Sustainability Disclosures in the Tech Sector: An AI-Based Assessment of Environmental Accountability
Author(s): Belgin Rana ÇARDAK, Hatice ÇARDAK, Özge Sezgin ALP, Adalet HAZAR, Şenol BABUŞCUSubject(s): Economy, Supranational / Global Economy, Accounting - Business Administration, ICT Information and Communications Technologies, Green Transformation
Published by: RITHA Publishing
Keywords: sentiment analysis; BERT model; environmental sustainability; technology firms; ESG reporting;
Summary/Abstract: The technology acts as both a driver of environmental solutions through AI-driven climate modelling and a source of pressure via high energy consumption and carbon emissions. This study employs a BERT-based Natural Language Processing (NLP) architecture to conduct a sentiment analysis of environmental sustainability reports from leading technology firms. By evaluating the consistency of these disclosures and their alignment with sector-specific indicators, the research assesses the reliability of "green" narratives in high-growth sectors. The findings demonstrate that sentiment-based analysis can effectively identify patterns of reporting quality, which is essential for ensuring the financial sustainability and accountability of tech-driven economies. This study offers a structural framework for regulators and investors to utilize AI in verifying the integrity of sustainability reporting, particularly in transitional markets where transparency is a prerequisite for long-term economic stability.
Journal: Journal of Applied Economic Sciences (JAES)
- Issue Year: XXI/2026
- Issue No: 1(91)SI
- Page Range: 217-235
- Page Count: 19
- Language: English
