Corporate Social Responsibility Reports: Understanding Topics via Text Mining

This study utilizes Text Data Mining (TDM) to analyze the contents of Corporate Social Responsibility (CSR) Reports. The goal is to find evidence that environmental sustainability has become embedded in corporate policy and the core business discourse of seven organizations over 2004-2012. Results from supervised modeling techniques suggest embeddedness of environmental qualities in the business discourse. Unsupervised techniques provide additional support for embeddedness—as business topics tend to increasingly group with environmental ones. The process we outline should facilitate pattern discovery in documents, minimizing or eliminating the need for time-consuming content analysis that is frequently used in qualitative research. To our knowledge, this is one of the first attempts to apply TDM processing to analyze unstructured data from CSR reports.

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