Corporate social responsibility disclosure on Twitter: Signalling or greenwashing? Evidence from the UK

• Published in: International journal of finance and economics Vol. 29; no. 2; pp. 1745 - 1761
• Main Authors: Amin, Marian H., Ali, Heba, Mohamed, Ehab K. A.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.04.2024; Wiley Periodicals Inc
• Subjects: corporate social responsibility; False information; greenwashing; machine learning; signalling theory; Social networks; Social responsibility; Twitter; United Kingdom > UK
• ISSN: 1076-9307; 1099-1158
• DOI: 10.1002/ijfe.2762

This study aims at exploring and investigating whether disclosure of corporate social responsibility (CSR) on Twitter signals true CSR performance or merely is a greenwashing tool to conceal and compensate for inferior CSR performance. Based on a sample of 167,908 tweets posted by the constituents of the FTSE 350 Index, topic modelling—a natural language processing technique based on unsupervised learning—is utilized to identify CSR disclosure on social media. Our empirical evidence based on several regression models shows association between firms' CSR performance and disclosure, which supports the signalling story, and hence, casts doubt on the greenwashing behaviour among UK firms on social media. Our findings suggest several implications for researchers, shareholders, and practitioners as the relation between CSR disclosure on influential, widely reached platforms such as social media and CSR performance carries important indications about the credibility of the content of such disclosure, the extent to which it reflects actual CSR performance, and hence its usefulness for all stakeholders interested in CSR. The true motive behind CSR disclosures can greatly influence how stakeholders perceive such information and the extent to which they can rely on it for decision making purposes.