Investigating corporate sustainability disclosure: a text mining analysis of non-financial reporting

Abstract

In recent years, the European Union (EU) has strengthened its legal framework for the disclosure of sustainability information, culminating in the Corporate Sustainability Reporting Directive (CSRD). This follows on from the previous Non-financial Reporting Directive (NFRD), which was implemented in Italy by Legislative Decree 254/2016 and requires large public interest entities to disclose non-financial information annually in the form of a non-financial statement (NFS). This study analyzes how the content of Italian companies’ NFS has evolved from 2019 to 2022, focusing on a preliminary analysis of 15 companies from the energy and textile sectors. The aim is to assess whether the reporting obligation has led to real improvements in sustainable communication or whether companies have limited themselves to formal compliance. Text mining techniques were used to analyze a corpus of NFSs using tools such as the term-document matrix, the term frequency – inverse document frequency (TF-IDF) algorithm, network graph analysis, and the structural topic model. The results show that the content of the NFS is increasingly enriched in both quantitative and qualitative terms, reflecting a stronger alignment with stakeholder expectations and regulatory objectives. Differences between sectors were also identified using dissimilarity indices, which show how sector-specific dynamics shape the representation of sustainability. This study contributes to the literature on non-financial reporting by demonstrating how automated text analysis can uncover meaningful patterns in corporate reporting. The methodology provides useful insights for regulators, policymakers, and companies seeking to improve sustainable reporting practices. Benchmarking based on such analyses can support the development of more transparent and effective sustainability strategies