Using the novel technique of topic modelling, this paper examines thematic patterns and their changes over time in a large corpus of corporate social responsibility (CSR) reports produced in the oil sector. Whereas previous research on corporate communications has been small-scale or interested in selected lexical aspects and thematic categories identified ex ante, our approach allows for thematic patterns to emerge from the data. The analysis reveals a number of major trends and topic shifts pointing to changing practices of CSR. Nowadays ‘people’, ‘communities’, and ‘rights’ seem to be given more prominence, whereas ‘environmental protection’ appears to be less relevant. Using more established corpus-based methods, we subsequently explore two top phrases—‘human rights’ and ‘climate change’—that were identified as representative of the shifting thematic patterns. Our approach strikes a balance between the purely quantitative and qualitative methodologies and offers applied linguists new ways of exploring discourse in large collections of texts.

This paper investigates the relationship between corporate social and environmental performance and financial performance for a sample of publicly traded US real estate companies. Using the MSCI ESG (formerly KLD) database on seven Environmental, Social & Governance dimensions in the 2003–2010 period, and weighting the dimensions according to prominence in the real estate sector, we model Tobin's Q and annual total return in a panel data framework. The results indicate a positive relationship between ESG rating and Tobin's Q but this effect is driven by ESG concerns rather than strengths. Consistently across all model specifications, overall ESG ratings are associated with lower returns. Negative scores appear to result in higher returns, at least in the short run, but positive scores have no significant impact on returns.