The aim of this paper is to contrast content analysis and text mining as two different research techniques both used by scholars to analyse company social and environmental reports. The paper starts with a presentation of the two research techniques commonly used in the analysis of corporate disclosure with special emphasis on social and environmental reporting. It examines the techniques with respect to the assumption each holds about the nature of knowledge and it continues with a discussion of the elements that display the differences and similarities between them. This theoretical part is enriched by a comparison in frequency usage and fields of applications of the two techniques. Then, the paper presents an empirical application of the two techniques to the same set of company reports published by four large multinationals that went through an industrial disaster characterized by negative social and environmental consequences with the aim to analyse changes in company social disclosure after the disaster. Results from the application of the two techniques are compared to see whether they lead to different conclusions about company behaviour in trying to restore corporate reputation damaged by the disaster.
Key-Words: Financial Reporting, text mining, content analysis, legitimacy theory, sustainability reporting, disaster, crisis
