Text Analytics Approach to Examining Corporate Social Responsibility

This research article explores a text analytics approach to assess the prominence of corporate social responsibility in 554 Singapore-listed firms through a content analysis of the news. Instead of relying on publications by the firms, third-party news coverage is used to reduce potential biases due to over-reporting. A dataset of news articles on the included firms published during fiscal years 2015 and 2016 is crawled, and the articles’ content is parsed to search for information related to corporate social responsibility. Graph theory is subsequently used to create a collaborative network of listed firms’ corporate social responsibility activities. The results highlight a more automated and scalable means of assessing the prominence of corporate social responsibility, as well as potential “influencers” within the corporate landscape.

Keywords: Corporate social responsibility; news; content analysis; collaborative network; Singapore Exchange

Suggested Citation: Suggested Citation

Azhar, Nurul Asyikeen and Pan, Gary and Seow, Poh-Sun and Koh, Andrew and Tay, Wan-Ying, Text Analytics Approach to Examining Corporate Social Responsibility (April 1, 2019). Asian Journal of Accounting and Governance, Vol. 11:85-96, Singapore Management University School of Accountancy Research Paper No. 2020-116, Available at SSRN: https://ssrn.com/abstract=3392876